Simulating Class Security With Python Machine Learning & Arduino (Pranav Sai)

💻 Github: https://github.com/psai-github/A.I-Classroom-Security (Pranav Sai)

Computer Vision with Machine Learning | Building My own AI Home Assistant | Ghost AI

We're currently building our own AI system called Ghost, he will control my home using modern Machine Learning and today we're focusing on computer vision! DISCORD: https://discord.gg/BYGkHuGWAe // FOLLOW ME ON TWITTER https://twitter.com/tyler_potts_ // CHECK OUT MY GAME https://play.google.com/store/apps/details?id=com.TylerPottsDev.BananaToss // DO THESE SIMPLE STEPS LIKE, SUBSCRIBE & SHARE #web #buildinpublic #saas

What Is Machine Learning? | Machine Learning Tutorial

This Machine Learning basics video will help you understand what is Machine Learning, what are the types of Machine Learning - supervised, unsupervised & reinforcement learning, how Machine Learning works with simple examples, and will also explain how Machine Learning is being used in various industries. Machine learning is a core sub-area of artificial intelligence; it enables computers to get into a mode of self-learning without being explicitly programmed. When exposed to new data, these computer programs are enabled to learn, grow, change, and develop by themselves. So, put simply, the iterative aspect of machine learning is the ability to adapt to new data independently. This is possible as programs learn from previous computations and use “pattern recognition” to produce reliable results. A form of artificial intelligence, Machine Learning is revolutionizing the world of computing and all people’s digital interactions. Machine Learning powers such innovative automated technologies as recommendation engines, facial recognition, fraud protection, and even self-driving cars. This Machine Learning course prepares engineers, data scientists, and other professionals with the knowledge and hands-on skills required for certification and job competency in Machine Learning. Why learn Machine Learning? Machine Learning is taking over the world- and with that, there is a growing need among companies for professionals to know the ins and outs of Machine Learning. The Machine Learning market size is expected to grow from USD 1.03 Billion in 2016 to USD 8.81 Billion by 2022, at a Compound Annual Growth Rate (CAGR) of 44.1% during the forecast period. What skills will you learn from this Machine Learning course? By the end of this Machine Learning course, you will be able to: 1. Master the concepts of supervised, unsupervised and reinforcement learning concepts and modeling. 2. Gain practical mastery over principles, algorithms, and applications of Machine Learning through a hands-on approach which includes working on 28 projects and one capstone project. 3. Acquire a thorough knowledge of the mathematical and heuristic aspects of Machine Learning. 4. Understand the concepts and operation of support vector machines, kernel SVM, naive Bayes, decision tree classifier, random forest classifier, logistic regression, K-nearest neighbors, K-means clustering and more. 5. Be able to model a wide variety of robust Machine Learning algorithms including deep learning, clustering, and recommendation systems We recommend this Machine Learning training course for the following professionals in particular: 1. Developers aspiring to be a data scientist or Machine Learning engineer 2. Information architects who want to gain expertise in Machine Learning algorithms 3. Analytics professionals who want to work in Machine Learning or artificial intelligence 4. Graduates looking to build a career in data science and Machine Learning

AI And Machine Learning Full Course 2022 AI Tutorial Machine Learning Tutorial

AI And Machine Learning Full Course 2022 AI Tutorial Machine Learning Tutorial This Artificial Intelligence and Machine Learning full course video cover all the topics that you need to know to become a master in the field of AI and Machine Learning. It covers all the basics of Machine Learning, the different types of Machine Learning, and the various applications of Machine Learning used in different industries. This video will also help us understand the basics of artificial intelligence. We will look at the future of AI and listen to some of the industry experts and learn what they have to say about AI. Finally, you will learn the Top 10 Artificial Intelligence Technologies In 2021. ✅Subscribe to our Channel to learn more about the top Technologies: What Exactly is Machine Learning? A good start at a Machine Learning definition is that it is a core sub-area of Artificial Intelligence (AI). ML applications learn from experience (well data) like humans without direct programming. When exposed to new data, these applications learn, grow, change, and develop by themselves. In other words, with Machine Learning, computers find insightful information without being told where to look. Instead, they do this by leveraging algorithms that learn from data in an iterative process. What is Artificial Intelligence? Artificial Intelligence is a method of making a computer, a computer-controlled robot, or software think intelligently like the human mind. AI is accomplished by studying the patterns of the human brain and by analyzing the cognitive process. The outcome of these studies develops intelligent software and systems. About Artificial Intelligence Course: This Introduction to Artificial Intelligence (AI) is designed to help learners decode the mystery of artificial intelligence and its business applications. This AI for beginners course provides an overview of AI concepts and workflows, machine learning, deep learning, and performance metrics. This Introduction to AI provides an overview of AI concepts and workflows, machine learning, deep learning, and performance metrics. You’ll learn the difference between supervised, unsupervised, and reinforcement learning; be exposed to use cases, and see how clustering and classification algorithms help identify AI business applications. Key Features: ✅ 3.5 hours of enriched learning ✅ Lifetime access to self-paced learning ✅ Industry-recognized course completion certificate Eligibility: This Introduction to AI for beginners is ideal for developers aspiring to be AI engineers, as well as for analytics managers, information architects, analytics professionals, and graduates looking to build a career in artificial intelligence or machine learning. Pre-requisites: There are no prerequisites for opting for this Introduction to Artificial Intelligence for beginners. It does not require programming or IT background, making it ideal for professionals from all walks of corporate life. DISCLAIMER – WORLD BEST DIGITAL DEMO YouTube channel didn't owned and received any audio and content rights of this audio book in given video. Its entire content and copyrights belongs to owners of this Audio Book. World best digital demo YouTube channel just promoting this video for their viewers for only the purpose of Spreading Positivity and Rightly educate masses about Direct Selling / Network Marketing / MLM by the help of this audio's as under Section 107 of the Copyright Act 1976. Allowance is made for "Fair-use" for purpose such as criticism, comment, news reporting, teaching, scholarship, and research. Fair use is a use permitted by copyright that might infringing, Non-profit, educational and personal use tips to balance in favour of fair use. If any dispute against this video on world best digital demo YouTube channel so kindly write us at mukesh10up@gmail.com will resolve or remove it. About world best digital demo: This educational channel provides a unique and accessible videos review so that these important literary works can be available to everyone. With each rare and often never-before-seen videos, Our library is for the academic study and for those that are seekers of wisdom, personal transformation, and self-improvement. Please participate by subscribing and sharing your thoughts in the comments section. THANK YOU FOR WATCHING THIS VIDEO: LOTS OF LOVE & THANKS

What Is Machine Learning? | Machine Learning Tutorial

This Machine Learning basics video will help you understand what is Machine Learning, what are the types of Machine Learning - supervised, unsupervised & reinforcement learning, how Machine Learning works with simple examples, and will also explain how Machine Learning is being used in various industries. Machine learning is a core sub-area of artificial intelligence; it enables computers to get into a mode of self-learning without being explicitly programmed. When exposed to new data, these computer programs are enabled to learn, grow, change, and develop by themselves. So, put simply, the iterative aspect of machine learning is the ability to adapt to new data independently. This is possible as programs learn from previous computations and use “pattern recognition” to produce reliable results. A form of artificial intelligence, Machine Learning is revolutionizing the world of computing and all people’s digital interactions. Machine Learning powers such innovative automated technologies as recommendation engines, facial recognition, fraud protection, and even self-driving cars. This Machine Learning course prepares engineers, data scientists, and other professionals with the knowledge and hands-on skills required for certification and job competency in Machine Learning. Why learn Machine Learning? Machine Learning is taking over the world- and with that, there is a growing need among companies for professionals to know the ins and outs of Machine Learning. The Machine Learning market size is expected to grow from USD 1.03 Billion in 2016 to USD 8.81 Billion by 2022, at a Compound Annual Growth Rate (CAGR) of 44.1% during the forecast period. What skills will you learn from this Machine Learning course? By the end of this Machine Learning course, you will be able to: 1. Master the concepts of supervised, unsupervised and reinforcement learning concepts and modeling. 2. Gain practical mastery over principles, algorithms, and applications of Machine Learning through a hands-on approach which includes working on 28 projects and one capstone project. 3. Acquire a thorough knowledge of the mathematical and heuristic aspects of Machine Learning. 4. Understand the concepts and operation of support vector machines, kernel SVM, naive Bayes, decision tree classifier, random forest classifier, logistic regression, K-nearest neighbors, K-means clustering and more. 5. Be able to model a wide variety of robust Machine Learning algorithms including deep learning, clustering, and recommendation systems We recommend this Machine Learning training course for the following professionals in particular: 1. Developers aspiring to be a data scientist or Machine Learning engineer 2. Information architects who want to gain expertise in Machine Learning algorithms 3. Analytics professionals who want to work in Machine Learning or artificial intelligence 4. Graduates looking to build a career in data science and Machine Learning

Is Google’s New AI As Smart As A Human? 🤖

❤️ Check out Fully Connected by Weights & Biases: https://wandb.me/papers 📝 The paper "Minerva - Solving Quantitative Reasoning Problems with Language Models" is available here: https://ift.tt/dNEVmoC ❤️ Watch these videos in early access on our Patreon page or join us here on YouTube: - https://ift.tt/Xaep89c - https://www.youtube.com/channel/UCbfYPyITQ-7l4upoX8nvctg/join 🙏 We would like to thank our generous Patreon supporters who make Two Minute Papers possible: Aleksandr Mashrabov, Alex Balfanz, Alex Haro, Andrew Melnychuk, Benji Rabhan, Bryan Learn, B Shang, Christian Ahlin, Eric Martel, Geronimo Moralez, Gordon Child, Ivo Galic, Jace O'Brien, Jack Lukic, John Le, Jonas, Jonathan, Kenneth Davis, Klaus Busse, Kyle Davis, Lorin Atzberger, Lukas Biewald, Matthew Allen Fisher, Michael Albrecht, Michael Tedder, Nevin Spoljaric, Nikhil Velpanur, Owen Campbell-Moore, Owen Skarpness, Rajarshi Nigam, Ramsey Elbasheer, Steef, Taras Bobrovytsky, Ted Johnson, Thomas Krcmar, Timothy Sum Hon Mun, Torsten Reil, Tybie Fitzhugh, Ueli Gallizzi. If you wish to appear here or pick up other perks, click here: https://ift.tt/Xaep89c Thumbnail background design: Felícia Zsolnai-Fehér - http://felicia.hu Károly Zsolnai-Fehér's links: Instagram: https://ift.tt/qNnfUGv Twitter: https://twitter.com/twominutepapers Web: https://ift.tt/McKYbUR

Build your first Machine Learning/AI model in 1 minute

Here is how you can build your first Machine Learning/AI model in 1 minute using Google's Teachable Machine Instagram: https://www.instagram.com/datascientist.py Setup and Wallpaper: https://beacons.ai/datascientist.py

AI And Machine Learning Full Course 2022 AI Tutorial Machine Learning Tutorial

AI And Machine Learning Full Course 2022 AI Tutorial Machine Learning Tutorial This Artificial Intelligence and Machine Learning full course video cover all the topics that you need to know to become a master in the field of AI and Machine Learning. It covers all the basics of Machine Learning, the different types of Machine Learning, and the various applications of Machine Learning used in different industries. This video will also help us understand the basics of artificial intelligence. We will look at the future of AI and listen to some of the industry experts and learn what they have to say about AI. Finally, you will learn the Top 10 Artificial Intelligence Technologies In 2021. ✅Subscribe to our Channel to learn more about the top Technologies: What Exactly is Machine Learning? A good start at a Machine Learning definition is that it is a core sub-area of Artificial Intelligence (AI). ML applications learn from experience (well data) like humans without direct programming. When exposed to new data, these applications learn, grow, change, and develop by themselves. In other words, with Machine Learning, computers find insightful information without being told where to look. Instead, they do this by leveraging algorithms that learn from data in an iterative process. What is Artificial Intelligence? Artificial Intelligence is a method of making a computer, a computer-controlled robot, or software think intelligently like the human mind. AI is accomplished by studying the patterns of the human brain and by analyzing the cognitive process. The outcome of these studies develops intelligent software and systems. About Artificial Intelligence Course: This Introduction to Artificial Intelligence (AI) is designed to help learners decode the mystery of artificial intelligence and its business applications. This AI for beginners course provides an overview of AI concepts and workflows, machine learning, deep learning, and performance metrics. This Introduction to AI provides an overview of AI concepts and workflows, machine learning, deep learning, and performance metrics. You’ll learn the difference between supervised, unsupervised, and reinforcement learning; be exposed to use cases, and see how clustering and classification algorithms help identify AI business applications. Key Features: ✅ 3.5 hours of enriched learning ✅ Lifetime access to self-paced learning ✅ Industry-recognized course completion certificate Eligibility: This Introduction to AI for beginners is ideal for developers aspiring to be AI engineers, as well as for analytics managers, information architects, analytics professionals, and graduates looking to build a career in artificial intelligence or machine learning. Pre-requisites: There are no prerequisites for opting for this Introduction to Artificial Intelligence for beginners. It does not require programming or IT background, making it ideal for professionals from all walks of corporate life. DISCLAIMER – WORLD BEST DIGITAL DEMO YouTube channel didn't owned and received any audio and content rights of this audio book in given video. Its entire content and copyrights belongs to owners of this Audio Book. World best digital demo YouTube channel just promoting this video for their viewers for only the purpose of Spreading Positivity and Rightly educate masses about Direct Selling / Network Marketing / MLM by the help of this audio's as under Section 107 of the Copyright Act 1976. Allowance is made for "Fair-use" for purpose such as criticism, comment, news reporting, teaching, scholarship, and research. Fair use is a use permitted by copyright that might infringing, Non-profit, educational and personal use tips to balance in favour of fair use. If any dispute against this video on world best digital demo YouTube channel so kindly write us at mukesh10up@gmail.com will resolve or remove it. About world best digital demo: This educational channel provides a unique and accessible videos review so that these important literary works can be available to everyone. With each rare and often never-before-seen videos, Our library is for the academic study and for those that are seekers of wisdom, personal transformation, and self-improvement. Please participate by subscribing and sharing your thoughts in the comments section. THANK YOU FOR WATCHING THIS VIDEO: LOTS OF LOVE & THANKS

🔥Top 8 Machine Learning Algorithms To Master in 2022 Machine Learning Tutorial

🔥Top 8 Machine Learning Algorithms To Master in 2022 Machine Learning Tutorial This video on Top 8 Machine Learning Algorithms to Master in 2022 is curated in collaboration with real-time industry experts to teach the learners about the critical fundamentals of machine learning. In this Machine LearningAlgorithms Full Course, you will learn in detail about the top Machine learning algorithms. You will start by understanding the basics of machine learning and know the essential applications of machine learning. You will know the machine learning concepts and then focus on some important machine learning algorithms using Python. What is Machine Learning? A good start at a Machine Learning definition is that it is a core sub-area of Artificial Intelligence (AI). ML applications learn from experience (data) like humans without direct programming. When exposed to new data, these applications learn, grow, change, and develop by themselves. What is Supervised Learning? In supervised learning, we use known or labeled data for training. Since the data is known, the learning is supervised, i.e., directed into successful execution. The input data goes through the Machine Learning algorithm and is used to train the model. What is Unsupervised Learning? In unsupervised learning, the training data is unknown and unlabeled - meaning that no one has looked at the data before. Without the aspect of known data, the input cannot be guided to the algorithm, which is where the unsupervised term originates from. What is Reinforcement Learning? The algorithm discovers data through a process of trial and error and then decides what action results in higher rewards. Three major components make up reinforcement learning: the agent, the environment, and the actions. The agent is the learner or decision-maker, the environment includes everything that the agent interacts with, and the actions are what the agent does. About Post Graduate Program in AI and Machine Learning: Fast track your career with our comprehensive Post Graduate Program in AI and Machine Learning, in partnership with Purdue University and in collaboration with IBM. This AI and machine learning certification program will prepare you for one of the world’s most exciting technology frontiers. This Post Graduate Program in AI and ML covers statistics, Python, machine learning, deep learning, NLP, and reinforcement learning. Key Features: ✅ Purdue Alumni Association Membership ✅ Industry-recognized IBM certificates for IBM courses ✅ Enrollment in Simplilearn’s JobAssist ✅ 25+ hands-on Projects on GPU-enabled Labs ✅ 450+ hours of Applied Learning ✅ Capstone Project in 3 Domains ✅ Purdue Post Graduate Program Certification ✅Get noticed by the top hiring companies DISCLAIMER – WORLD BEST DIGITAL DEMO YouTube channel didn't owned and received any audio and content rights of this audio book in given video. Its entire content and copyrights belongs to owners of this Audio Book. World best digital demo YouTube channel just promoting this video for their viewers for only the purpose of Spreading Positivity and Rightly educate masses about Direct Selling / Network Marketing / MLM by the help of this audio's as under Section 107 of the Copyright Act 1976. Allowance is made for "Fair-use" for purpose such as criticism, comment, news reporting, teaching, scholarship, and research. Fair use is a use permitted by copyright that might infringing, Non-profit, educational and personal use tips to balance in favour of fair use. If any dispute against this video on world best digital demo YouTube channel so kindly write us at mukesh10up@gmail.com will resolve or remove it. About world best digital demo: This educational channel provides a unique and accessible videos review so that these important literary works can be available to everyone. With each rare and often never-before-seen videos, Our library is for the academic study and for those that are seekers of wisdom, personal transformation, and self-improvement. Please participate by subscribing and sharing your thoughts in the comments section. THANK YOU FOR WATCHING THIS VIDEO: LOTS OF LOVE & THANKS

Build your first Machine Learning/AI model in 1 minute

Here is how you can build your first Machine Learning/AI model in 1 minute using Google's Teachable Machine Instagram: https://www.instagram.com/datascientist.py Setup and Wallpaper: https://beacons.ai/datascientist.py

Super resolution with UpscalerJS - Made with TensorFlow.js

Have you ever tried to scale a photo and the finished product comes out low quality? It lacks clarity, the colors are off, and you don’t even want to use it anymore. Meet Kevin Scott, ML Engineer behind UpscalerJS, an open source library that takes images and runs them through a neural network to increase image resolution up to 4x. Try it for yourself! Try it for yourself: Upscaler demo → https://goo.gle/3QrWCvH GitHub → https://goo.gle/3wp5lr5 Kevin’s TensorFlow.js book →https://goo.gle/3w7C6IK Want to be on the show? Use #MadeWithTFJS to share your own creations on social media and we may feature you in our next show. Catch more #MadeWithTFJS interviews → http://goo.gle/made-with-tfjs Subscribe to the TensorFlow channel → https://goo.gle/TensorFlow

🔥Machine Learning Tutorial 2022 Supervised Unsupervised Reinforcement Learning

🔥Machine Learning Tutorial 2022 Supervised Unsupervised Reinforcement Learning This video on Complete Machine Learning Tutorial to learn Supervised, Unsupervised, and Reinforced learning is curated in collaboration with real-time industry experts to teach the learners about the critical fundamentals of machine learning. In this Machine Learning Full Course video, you will learn about Supervised, Unsupervised and Reinforcement Learning in detail. You will start by understanding the basics of machine learning and know the essential applications of machine learning. You will know the machine learning concepts and then focus on some important machine learning algorithms using Python. What is Machine Learning? A good start at a Machine Learning definition is that it is a core sub-area of Artificial Intelligence (AI). ML applications learn from experience (well data) like humans without direct programming. When exposed to new data, these applications learn, grow, change, and develop by themselves. What is Supervised Learning? In supervised learning, we use known or labeled data for the training data. Since the data is known, the learning is, therefore, supervised, i.e., directed into successful execution. The input data goes through the Machine Learning algorithm and is used to train the model. What is Unsupervised Learning? In unsupervised learning, the training data is unknown and unlabeled - meaning that no one has looked at the data before. Without the aspect of known data, the input cannot be guided to the algorithm, which is where the unsupervised term originates from. What is Reinforcement Learning? The algorithm discovers data through a process of trial and error and then decides what action results in higher rewards. Three major components make up reinforcement learning: the agent, the environment, and the actions. The agent is the learner or decision-maker, the environment includes everything that the agent interacts with, and the actions are what the agent does. To learn more about Machine Learning, check our Post Graduate Program in AI and Machine Learning at: https://www.simplilearn.com/pgp-ai-ma... . About Post Graduate Program in AI and Machine Learning: Fast track your career with our comprehensive Post Graduate Program in AI and Machine Learning, in partnership with Purdue University and in collaboration with IBM. This AI and machine learning certification program will prepare you for one of the world’s most exciting technology frontiers. This Post Graduate Program in AI and ML covers statistics, Python, machine learning, deep learning, NLP, and reinforcement learning. Key Features: ✅ Purdue Alumni Association Membership ✅ Industry-recognized IBM certificates for IBM courses ✅ Enrollment in Simplilearn’s JobAssist ✅ 25+ hands-on Projects on GPU-enabled Labs ✅ 450+ hours of Applied Learning ✅ Capstone Project in 3 Domains ✅ Purdue Post Graduate Program Certification ✅Get noticed by the top hiring companies DISCLAIMER – WORLD BEST DIGITAL DEMO YouTube channel didn't owned and received any audio and content rights of this audio book in given video. Its entire content and copyrights belongs to owners of this Audio Book. World best digital demo YouTube channel just promoting this video for their viewers for only the purpose of Spreading Positivity and Rightly educate masses about Direct Selling / Network Marketing / MLM by the help of this audio's as under Section 107 of the Copyright Act 1976. Allowance is made for "Fair-use" for purpose such as criticism, comment, news reporting, teaching, scholarship, and research. Fair use is a use permitted by copyright that might infringing, Non-profit, educational and personal use tips to balance in favour of fair use. If any dispute against this video on world best digital demo YouTube channel so kindly write us at mukesh10up@gmail.com will resolve or remove it. About world best digital demo: This educational channel provides a unique and accessible videos review so that these important literary works can be available to everyone. With each rare and often never-before-seen videos, Our library is for the academic study and for those that are seekers of wisdom, personal transformation, and self-improvement. Please participate by subscribing and sharing your thoughts in the comments section. THANK YOU FOR WATCHING THIS VIDEO: LOTS OF LOVE & THANKS

Artificial Intelligence In 6 Minutes | What Is Artificial Intelligence? | AI Tutorial |

In this video on Artificial Intelligence, we will answer the question which has been in everyone's mind since the recent AI boom: "What Is Artificial Intelligence?". We will look at the factors which determine intelligent systems and take a look at the various sub-branches of AI. We will then dive into the future and look at where AI is expected to reach in a few years. What is Artificial Intelligence? Artificial Intelligence or AI is the combination of algorithms used for the purpose of creating intelligent machines that have the same skills as a human being. It uses machine learning and deep learning techniques to build complex systems. AI has made significant advances in the past few years and has impacted both our everyday lives and business in big ways. It is being widely used in every sector of business, such as Healthcare, E-Commerce, Manufacturing, Retail, and Logistics. Simplilearn’s Artificial Intelligence course provides training in the skills required for a career in AI. You will master TensorFlow, Machine Learning and other AI concepts, plus the programming languages needed to design intelligent agents, deep learning algorithms & advanced artificial neural networks that use predictive analytics to solve real-time decision-making problems without explicit programming. Why learn Artificial Intelligence? The current and future demand for AI engineers is staggering. The New York Times reports a candidate shortage for certified AI Engineers, with fewer than 10,000 qualified people in the world to fill these jobs, which according to Paysa earn an average salary of $172,000 per year in the U.S. (or Rs.17 lakhs to Rs. 25 lakhs in India) for engineers with the required skills. You can gain in-depth knowledge of Artificial Intelligence by taking our Artificial Intelligence certification training course. Those who complete the course will be able to: 1. Master the concepts of supervised and unsupervised learning 2. Gain practical mastery over principles, algorithms, and applications of machine learning through a hands-on approach which includes working on 28 projects and one capstone project. 3. Acquire thorough knowledge of the mathematical and heuristic aspects of machine learning. 4. Understand the concepts and operation of support vector machines, kernel SVM, naive bayes, decision tree classifier, random forest classifier, logistic regression, K-nearest neighbors, K-means clustering and more. 5. Comprehend the theoretical concepts and how they relate to the practical aspects of machine learning. 6. Be able to model a wide variety of robust machine learning algorithms including deep learning, clustering, and recommendation systems

🔥Top 8 Machine Learning Algorithms To Master in 2022 Machine Learning Tutorial

🔥Top 8 Machine Learning Algorithms To Master in 2022 Machine Learning Tutorial This video on Top 8 Machine Learning Algorithms to Master in 2022 is curated in collaboration with real-time industry experts to teach the learners about the critical fundamentals of machine learning. In this Machine LearningAlgorithms Full Course, you will learn in detail about the top Machine learning algorithms. You will start by understanding the basics of machine learning and know the essential applications of machine learning. You will know the machine learning concepts and then focus on some important machine learning algorithms using Python. What is Machine Learning? A good start at a Machine Learning definition is that it is a core sub-area of Artificial Intelligence (AI). ML applications learn from experience (data) like humans without direct programming. When exposed to new data, these applications learn, grow, change, and develop by themselves. What is Supervised Learning? In supervised learning, we use known or labeled data for training. Since the data is known, the learning is supervised, i.e., directed into successful execution. The input data goes through the Machine Learning algorithm and is used to train the model. What is Unsupervised Learning? In unsupervised learning, the training data is unknown and unlabeled - meaning that no one has looked at the data before. Without the aspect of known data, the input cannot be guided to the algorithm, which is where the unsupervised term originates from. What is Reinforcement Learning? The algorithm discovers data through a process of trial and error and then decides what action results in higher rewards. Three major components make up reinforcement learning: the agent, the environment, and the actions. The agent is the learner or decision-maker, the environment includes everything that the agent interacts with, and the actions are what the agent does. About Post Graduate Program in AI and Machine Learning: Fast track your career with our comprehensive Post Graduate Program in AI and Machine Learning, in partnership with Purdue University and in collaboration with IBM. This AI and machine learning certification program will prepare you for one of the world’s most exciting technology frontiers. This Post Graduate Program in AI and ML covers statistics, Python, machine learning, deep learning, NLP, and reinforcement learning. Key Features: ✅ Purdue Alumni Association Membership ✅ Industry-recognized IBM certificates for IBM courses ✅ Enrollment in Simplilearn’s JobAssist ✅ 25+ hands-on Projects on GPU-enabled Labs ✅ 450+ hours of Applied Learning ✅ Capstone Project in 3 Domains ✅ Purdue Post Graduate Program Certification ✅Get noticed by the top hiring companies DISCLAIMER – WORLD BEST DIGITAL DEMO YouTube channel didn't owned and received any audio and content rights of this audio book in given video. Its entire content and copyrights belongs to owners of this Audio Book. World best digital demo YouTube channel just promoting this video for their viewers for only the purpose of Spreading Positivity and Rightly educate masses about Direct Selling / Network Marketing / MLM by the help of this audio's as under Section 107 of the Copyright Act 1976. Allowance is made for "Fair-use" for purpose such as criticism, comment, news reporting, teaching, scholarship, and research. Fair use is a use permitted by copyright that might infringing, Non-profit, educational and personal use tips to balance in favour of fair use. If any dispute against this video on world best digital demo YouTube channel so kindly write us at mukesh10up@gmail.com will resolve or remove it. About world best digital demo: This educational channel provides a unique and accessible videos review so that these important literary works can be available to everyone. With each rare and often never-before-seen videos, Our library is for the academic study and for those that are seekers of wisdom, personal transformation, and self-improvement. Please participate by subscribing and sharing your thoughts in the comments section. THANK YOU FOR WATCHING THIS VIDEO: LOTS OF LOVE & THANKS

Study with Me - Fast.AI's Deep Learning Course - 3. Deep Neural Networks

This is a self-commitment series where I'm going to publish the videos of me just attending/watching Jeremy Howard's latest Deep Learning Course. Honestly, I hate study with me videos by productivity gurus, but I'm publishing this solely for my self-discipline and commitment to finish the course after multiple failed attempts. Fast.ai Practical Deep Learning for Coders Course - https://course.fast.ai/ Notion Notes: https://www.notion.so/Lesson-3-9988c7df1d274f059e141c32c134c53a

Design Calculator GUI using PYTHON #python #pythoncode #machinelearning #blockchain #AI

Build Calculator using PYTHON #python #pythoncode #machinelearning #blockchain #AI #artificialintelligence #pythonprogramming #artificialintelligence #8051 #8086 #microcontroller #arduino

🔥Machine Learning Tutorial 2022 Supervised Unsupervised Reinforcement Learning

🔥Machine Learning Tutorial 2022 Supervised Unsupervised Reinforcement Learning This video on Complete Machine Learning Tutorial to learn Supervised, Unsupervised, and Reinforced learning is curated in collaboration with real-time industry experts to teach the learners about the critical fundamentals of machine learning. In this Machine Learning Full Course video, you will learn about Supervised, Unsupervised and Reinforcement Learning in detail. You will start by understanding the basics of machine learning and know the essential applications of machine learning. You will know the machine learning concepts and then focus on some important machine learning algorithms using Python. What is Machine Learning? A good start at a Machine Learning definition is that it is a core sub-area of Artificial Intelligence (AI). ML applications learn from experience (well data) like humans without direct programming. When exposed to new data, these applications learn, grow, change, and develop by themselves. What is Supervised Learning? In supervised learning, we use known or labeled data for the training data. Since the data is known, the learning is, therefore, supervised, i.e., directed into successful execution. The input data goes through the Machine Learning algorithm and is used to train the model. What is Unsupervised Learning? In unsupervised learning, the training data is unknown and unlabeled - meaning that no one has looked at the data before. Without the aspect of known data, the input cannot be guided to the algorithm, which is where the unsupervised term originates from. What is Reinforcement Learning? The algorithm discovers data through a process of trial and error and then decides what action results in higher rewards. Three major components make up reinforcement learning: the agent, the environment, and the actions. The agent is the learner or decision-maker, the environment includes everything that the agent interacts with, and the actions are what the agent does. To learn more about Machine Learning, check our Post Graduate Program in AI and Machine Learning at: https://www.simplilearn.com/pgp-ai-ma... . About Post Graduate Program in AI and Machine Learning: Fast track your career with our comprehensive Post Graduate Program in AI and Machine Learning, in partnership with Purdue University and in collaboration with IBM. This AI and machine learning certification program will prepare you for one of the world’s most exciting technology frontiers. This Post Graduate Program in AI and ML covers statistics, Python, machine learning, deep learning, NLP, and reinforcement learning. Key Features: ✅ Purdue Alumni Association Membership ✅ Industry-recognized IBM certificates for IBM courses ✅ Enrollment in Simplilearn’s JobAssist ✅ 25+ hands-on Projects on GPU-enabled Labs ✅ 450+ hours of Applied Learning ✅ Capstone Project in 3 Domains ✅ Purdue Post Graduate Program Certification ✅Get noticed by the top hiring companies DISCLAIMER – WORLD BEST DIGITAL DEMO YouTube channel didn't owned and received any audio and content rights of this audio book in given video. Its entire content and copyrights belongs to owners of this Audio Book. World best digital demo YouTube channel just promoting this video for their viewers for only the purpose of Spreading Positivity and Rightly educate masses about Direct Selling / Network Marketing / MLM by the help of this audio's as under Section 107 of the Copyright Act 1976. Allowance is made for "Fair-use" for purpose such as criticism, comment, news reporting, teaching, scholarship, and research. Fair use is a use permitted by copyright that might infringing, Non-profit, educational and personal use tips to balance in favour of fair use. If any dispute against this video on world best digital demo YouTube channel so kindly write us at mukesh10up@gmail.com will resolve or remove it. About world best digital demo: This educational channel provides a unique and accessible videos review so that these important literary works can be available to everyone. With each rare and often never-before-seen videos, Our library is for the academic study and for those that are seekers of wisdom, personal transformation, and self-improvement. Please participate by subscribing and sharing your thoughts in the comments section. THANK YOU FOR WATCHING THIS VIDEO: LOTS OF LOVE & THANKS

Artificial Intelligence In 6 Minutes | What Is Artificial Intelligence? | AI Tutorial |

In this video on Artificial Intelligence, we will answer the question which has been in everyone's mind since the recent AI boom: "What Is Artificial Intelligence?". We will look at the factors which determine intelligent systems and take a look at the various sub-branches of AI. We will then dive into the future and look at where AI is expected to reach in a few years. What is Artificial Intelligence? Artificial Intelligence or AI is the combination of algorithms used for the purpose of creating intelligent machines that have the same skills as a human being. It uses machine learning and deep learning techniques to build complex systems. AI has made significant advances in the past few years and has impacted both our everyday lives and business in big ways. It is being widely used in every sector of business, such as Healthcare, E-Commerce, Manufacturing, Retail, and Logistics. Simplilearn’s Artificial Intelligence course provides training in the skills required for a career in AI. You will master TensorFlow, Machine Learning and other AI concepts, plus the programming languages needed to design intelligent agents, deep learning algorithms & advanced artificial neural networks that use predictive analytics to solve real-time decision-making problems without explicit programming. Why learn Artificial Intelligence? The current and future demand for AI engineers is staggering. The New York Times reports a candidate shortage for certified AI Engineers, with fewer than 10,000 qualified people in the world to fill these jobs, which according to Paysa earn an average salary of $172,000 per year in the U.S. (or Rs.17 lakhs to Rs. 25 lakhs in India) for engineers with the required skills. You can gain in-depth knowledge of Artificial Intelligence by taking our Artificial Intelligence certification training course. Those who complete the course will be able to: 1. Master the concepts of supervised and unsupervised learning 2. Gain practical mastery over principles, algorithms, and applications of machine learning through a hands-on approach which includes working on 28 projects and one capstone project. 3. Acquire thorough knowledge of the mathematical and heuristic aspects of machine learning. 4. Understand the concepts and operation of support vector machines, kernel SVM, naive bayes, decision tree classifier, random forest classifier, logistic regression, K-nearest neighbors, K-means clustering and more. 5. Comprehend the theoretical concepts and how they relate to the practical aspects of machine learning. 6. Be able to model a wide variety of robust machine learning algorithms including deep learning, clustering, and recommendation systems

Calculator GUI using PYTHON #python #pythoncode #machinelearning #blockchain #AI

Build Calculator using PYTHON #python #pythoncode #machinelearning #blockchain #AI #artificialintelligence #pythonprogramming #artificialintelligence #8051 #8086 #microcontroller #arduino

Microsoft's New AI: Virtual Humans Became Real! 🤯

❤️ Check out Runway and try it for free here: https://ift.tt/NcZrsVk 📝 The paper "3D Face Reconstruction with Dense Landmarks" is available here: https://ift.tt/f80vSx7 🙏 We would like to thank our generous Patreon supporters who make Two Minute Papers possible: Aleksandr Mashrabov, Alex Balfanz, Alex Haro, Andrew Melnychuk, Benji Rabhan, Bryan Learn, B Shang, Christian Ahlin, Eric Martel, Geronimo Moralez, Gordon Child, Ivo Galic, Jace O'Brien, Jack Lukic, John Le, Jonas, Jonathan, Kenneth Davis, Klaus Busse, Kyle Davis, Lorin Atzberger, Lukas Biewald, Matthew Allen Fisher, Michael Albrecht, Michael Tedder, Nevin Spoljaric, Nikhil Velpanur, Owen Campbell-Moore, Owen Skarpness, Rajarshi Nigam, Ramsey Elbasheer, Steef, Taras Bobrovytsky, Ted Johnson, Thomas Krcmar, Timothy Sum Hon Mun, Torsten Reil, Tybie Fitzhugh, Ueli Gallizzi. If you wish to appear here or pick up other perks, click here: https://ift.tt/cQ8tpje Thumbnail background design: Felícia Zsolnai-Fehér - http://felicia.hu Károly Zsolnai-Fehér's links: Instagram: https://ift.tt/oYKSrcC Twitter: https://twitter.com/twominutepapers Web: https://ift.tt/CwmNhGn

Yoha: Write in thin air with custom hand tracking - Made with TensorFlow.js

Meet Benjamin Mularczyk, a software engineer based in Zürich, Switzerland who shares his hand detection software, Yoha, thats powered by a custom made TensorFlow.js model. Inspired by the whiteboard experience, Yoha detects your hand within a video stream and allows you to sketch with your hand in real time as visuals appear on the screen in front of you or to a remote audience. Learn how this hand tracking engine is using Web ML in the browser enabling anyone anywhere to try and use this technology at scale. Try it for yourself: Github → https://goo.gle/3LpjEjJ Website / demo → https://goo.gle/3sIf5KP Want to be on the show? Use #MadeWithTFJS or #WebML to share your own creations on social media and we may feature you in our next show. Catch more #MadeWithTFJS interviews → http://goo.gle/made-with-tfjs Subscribe to the TensorFlow channel → https://goo.gle/TensorFlow

Google’s New AI Learned To See In The Dark! 🤖

❤️ Check out Weights & Biases and sign up for a free demo here: https://ift.tt/ETAkZfc 📝 The paper "NeRF in the Dark: High Dynamic Range View Synthesis from Noisy Raw Images" is available here: https://ift.tt/rtzXCSV ❤️ Watch these videos in early access on our Patreon page or join us here on YouTube: - https://ift.tt/K8g4hiQ - https://www.youtube.com/channel/UCbfYPyITQ-7l4upoX8nvctg/join 🙏 We would like to thank our generous Patreon supporters who make Two Minute Papers possible: Aleksandr Mashrabov, Alex Balfanz, Alex Haro, Andrew Melnychuk, Benji Rabhan, Bryan Learn, B Shang, Christian Ahlin, Eric Martel, Geronimo Moralez, Gordon Child, Ivo Galic, Jace O'Brien, Jack Lukic, John Le, Jonas, Jonathan, Kenneth Davis, Klaus Busse, Kyle Davis, Lorin Atzberger, Lukas Biewald, Matthew Allen Fisher, Michael Albrecht, Michael Tedder, Nevin Spoljaric, Nikhil Velpanur, Owen Campbell-Moore, Owen Skarpness, Rajarshi Nigam, Ramsey Elbasheer, Steef, Taras Bobrovytsky, Ted Johnson, Thomas Krcmar, Timothy Sum Hon Mun, Torsten Reil, Tybie Fitzhugh, Ueli Gallizzi. If you wish to appear here or pick up other perks, click here: https://ift.tt/K8g4hiQ Thumbnail background design: Felícia Zsolnai-Fehér - http://felicia.hu Károly Zsolnai-Fehér's links: Instagram: https://ift.tt/oBs5DtK Twitter: https://twitter.com/twominutepapers Web: https://ift.tt/e38gCtb

Samsung’s AI: Megapixel DeepFakes! 📷

❤️ Check out Lambda here and sign up for their GPU Cloud: https://ift.tt/pZDwUkx 📝 The paper "MegaPortraits: One-shot Megapixel Neural Head Avatars" is available here: https://ift.tt/RGL9WQ4 ❤️ Watch these videos in early access on our Patreon page or join us here on YouTube: - https://ift.tt/i5N67cd - https://www.youtube.com/channel/UCbfYPyITQ-7l4upoX8nvctg/join 🙏 We would like to thank our generous Patreon supporters who make Two Minute Papers possible: Aleksandr Mashrabov, Alex Balfanz, Alex Haro, Andrew Melnychuk, Benji Rabhan, Bryan Learn, B Shang, Christian Ahlin, Eric Martel, Geronimo Moralez, Gordon Child, Ivo Galic, Jace O'Brien, Jack Lukic, John Le, Jonas, Jonathan, Kenneth Davis, Klaus Busse, Kyle Davis, Lorin Atzberger, Lukas Biewald, Matthew Allen Fisher, Michael Albrecht, Michael Tedder, Nevin Spoljaric, Nikhil Velpanur, Owen Campbell-Moore, Owen Skarpness, Rajarshi Nigam, Ramsey Elbasheer, Steef, Taras Bobrovytsky, Ted Johnson, Thomas Krcmar, Timothy Sum Hon Mun, Torsten Reil, Tybie Fitzhugh, Ueli Gallizzi. If you wish to appear here or pick up other perks, click here: https://ift.tt/i5N67cd Thumbnail background design: Felícia Zsolnai-Fehér - http://felicia.hu Károly Zsolnai-Fehér's links: Instagram: https://ift.tt/eXpVsuR Twitter: https://twitter.com/twominutepapers Web: https://ift.tt/qO54aCu #DeepFake

The Man behind Stable Diffusion

#stablediffusion #ai #stabilityai OUTLINE: 0:00 - Intro 1:30 - What is Stability AI? 3:45 - Where does the money come from? 5:20 - Is this the CERN of AI? 6:15 - Who gets access to the resources? 8:00 - What is Stable Diffusion? 11:40 - What if your model produces bad outputs? 14:20 - Do you employ people? 16:35 - Can you prevent the corruption of profit? 19:50 - How can people find you? 22:45 - Final thoughts, let's destroy PowerPoint Links: Homepage: https://ykilcher.com Merch: https://ift.tt/bIQCEWS YouTube: https://www.youtube.com/c/yannickilcher Twitter: https://twitter.com/ykilcher Discord: https://ift.tt/FZ3qzeN LinkedIn: https://ift.tt/4TrHCga If you want to support me, the best thing to do is to share out the content :) If you want to support me financially (completely optional and voluntary, but a lot of people have asked for this): SubscribeStar: https://ift.tt/EJ6BxQP Patreon: https://ift.tt/0fJ3mGe Bitcoin (BTC): bc1q49lsw3q325tr58ygf8sudx2dqfguclvngvy2cq Ethereum (ETH): 0x7ad3513E3B8f66799f507Aa7874b1B0eBC7F85e2 Litecoin (LTC): LQW2TRyKYetVC8WjFkhpPhtpbDM4Vw7r9m Monero (XMR): 4ACL8AGrEo5hAir8A9CeVrW8pEauWvnp1WnSDZxW7tziCDLhZAGsgzhRQABDnFy8yuM9fWJDviJPHKRjV4FWt19CJZN9D4n

Building and Working in Environments for Embodied AI | CVPR 2022 Tutorial

If you have any copyright issues on video, please send us an email at khawar512@gmail.com Top CV and PR Conferences: Publication h5-index h5-median 1. IEEE/CVF Conference on Computer Vision and Pattern Recognition 356 583 2. European Conference on Computer Vision 197 342 3. IEEE/CVF International Conference on Computer Vision 184 311 4. IEEE Transactions on Pattern Analysis and Machine Intelligence 149 275 5. IEEE Transactions on Image Processing 123 187 6. Pattern Recognition 99 141 7. IEEE/CVF Computer Society Conference on Computer Vision and Pattern Recognition Workshops (CVPRW) 89 154 8. Medical Image Analysis 76 149 9. International Journal of Computer Vision 72 173 10. British Machine Vision Conference (BMVC) 66 102 11. Pattern Recognition Letters 66 93 12. IEEE/CVF Winter Conference on Applications of Computer Vision (WACV) 62 121 13. IEEE International Conference on Image Processing (ICIP) 60 89 14. IEEE/CVF International Conference on Computer Vision Workshops (ICCVW) 57 83 15. Computer Vision and Image Understanding 52 91 16. Journal of Visual Communication and Image Representation 47 64 17. International Conference on 3D Vision (3DV) 44 89 18. International Conference on Pattern Recognition 43 78 19. Asian Conference on Computer Vision (ACCV) 43 69 20. IEEE International Conference on Automatic Face & Gesture Recognition 42 66 Top Papers at CVPR Deep Residual Learning for Image Recognition. Densely Connected Convolutional Networks. You Only Look Once: Unified, Real-Time Object Detection. Rethinking the Inception Architecture for Computer Vision. Image-to-Image Translation with Conditional Adversarial Networks. YOLO9000: Better, Faster, Stronger. Feature Pyramid Networks for Object Detection. Squeeze-and-Excitation Networks Photo-Realistic Single Image Super-Resolution Using a Generative Adversarial Network. Xception: Deep Learning with Depthwise Separable Convolutions. MobileNetV2: Inverted Residuals and Linear Bottlenecks The Cityscapes Dataset for Semantic Urban Scene Understanding. Pyramid Scene Parsing Network. PointNet: Deep Learning on Point Sets for 3D Classification and Segmentation. Aggregated Residual Transformations for Deep Neural Networks. Learning Deep Features for Discriminative Localization. Accurate Image Super-Resolution Using Very Deep Convolutional Networks. Realtime Multi-person 2D Pose Estimation Using Part Affinity Fields. Non-local Neural Networks Quo Vadis, Action Recognition? A New Model and the Kinetics Dataset.

Human-Centered AI for Computer Vision | CVPR 2022 Tutorial

If you have any copyright issues on video, please send us an email at khawar512@gmail.com Top CV and PR Conferences: Publication h5-index h5-median 1. IEEE/CVF Conference on Computer Vision and Pattern Recognition 356 583 2. European Conference on Computer Vision 197 342 3. IEEE/CVF International Conference on Computer Vision 184 311 4. IEEE Transactions on Pattern Analysis and Machine Intelligence 149 275 5. IEEE Transactions on Image Processing 123 187 6. Pattern Recognition 99 141 7. IEEE/CVF Computer Society Conference on Computer Vision and Pattern Recognition Workshops (CVPRW) 89 154 8. Medical Image Analysis 76 149 9. International Journal of Computer Vision 72 173 10. British Machine Vision Conference (BMVC) 66 102 11. Pattern Recognition Letters 66 93 12. IEEE/CVF Winter Conference on Applications of Computer Vision (WACV) 62 121 13. IEEE International Conference on Image Processing (ICIP) 60 89 14. IEEE/CVF International Conference on Computer Vision Workshops (ICCVW) 57 83 15. Computer Vision and Image Understanding 52 91 16. Journal of Visual Communication and Image Representation 47 64 17. International Conference on 3D Vision (3DV) 44 89 18. International Conference on Pattern Recognition 43 78 19. Asian Conference on Computer Vision (ACCV) 43 69 20. IEEE International Conference on Automatic Face & Gesture Recognition 42 66 Top Papers at CVPR Deep Residual Learning for Image Recognition. Densely Connected Convolutional Networks. You Only Look Once: Unified, Real-Time Object Detection. Rethinking the Inception Architecture for Computer Vision. Image-to-Image Translation with Conditional Adversarial Networks. YOLO9000: Better, Faster, Stronger. Feature Pyramid Networks for Object Detection. Squeeze-and-Excitation Networks Photo-Realistic Single Image Super-Resolution Using a Generative Adversarial Network. Xception: Deep Learning with Depthwise Separable Convolutions. MobileNetV2: Inverted Residuals and Linear Bottlenecks The Cityscapes Dataset for Semantic Urban Scene Understanding. Pyramid Scene Parsing Network. PointNet: Deep Learning on Point Sets for 3D Classification and Segmentation. Aggregated Residual Transformations for Deep Neural Networks. Learning Deep Features for Discriminative Localization. Accurate Image Super-Resolution Using Very Deep Convolutional Networks. Realtime Multi-person 2D Pose Estimation Using Part Affinity Fields. Non-local Neural Networks Quo Vadis, Action Recognition? A New Model and the Kinetics Dataset.

AI vs ML vs DL | ai vs ml | al vs ml vs deep learning | Difference between AI, ML & DL

#aivsmlvsdl #artificialintelligence #machinelearning #deeplearning #artificialintelligencevsmachinelearningvsdeeplearning #tutorial #basics #differences #ai #ml #dl #simple #beginners #aibasics #video #learn #learnai #learnml #learndl #easy #unfoldai #endtoend #jaanvi #aiexplained #english #guide #endtoend #mlcourse #beginnersguide #easy In this video we'll understand the relationship between artificial intelligence, machine learning and deep learning Introduction to artificial intelligence: https://youtu.be/blp9oB3zTKU

[ML News] AI models that write code (Copilot, CodeWhisperer, Pangu-Coder, etc.)

#mlnews #ai #copilot OUTLINE: 0:00 - Intro 0:20 - Copilot Now Generally Available 3:20 - FOSS Org leaves GitHub 6:45 - Google's Internal ML Code Completion 9:10 - AI Trains Itself to Code Better 14:30 - Amazon CodeWhisperer in Preview 15:15 - Pangu-Coder: A New Coding Model 17:10 - Useful Things References: Copilot Now Generally Available https://ift.tt/TFvhDdw FOSS Org leaves GitHub https://ift.tt/l8xJgzF https://ift.tt/FgzimNK https://ift.tt/O3v8zEX https://ift.tt/Zu6m3RH Google's Internal ML Code Completion https://ift.tt/6FLE90d AI Trains Itself to Code Better https://ift.tt/wNPmIDe https://ift.tt/TCtNxuS Amazon CodeWhisperer in Preview https://ift.tt/MEsCgUS https://ift.tt/ankmVhL https://ift.tt/rZtsOX3 Pangu-Coder: A New Coding Model https://ift.tt/GI9KF7g https://ift.tt/N15ewRj Useful Things https://ift.tt/51JhWXA https://ift.tt/jYe1Eai https://ift.tt/KLsJaSr https://ift.tt/QYypCP2 Links: Homepage: https://ykilcher.com Merch: https://ift.tt/a2P1dgK YouTube: https://www.youtube.com/c/yannickilcher Twitter: https://twitter.com/ykilcher Discord: https://ift.tt/gj16i50 LinkedIn: https://ift.tt/Asl3ZDx If you want to support me, the best thing to do is to share out the content :) If you want to support me financially (completely optional and voluntary, but a lot of people have asked for this): SubscribeStar: https://ift.tt/efoVMpl Patreon: https://ift.tt/vVLisOW Bitcoin (BTC): bc1q49lsw3q325tr58ygf8sudx2dqfguclvngvy2cq Ethereum (ETH): 0x7ad3513E3B8f66799f507Aa7874b1B0eBC7F85e2 Litecoin (LTC): LQW2TRyKYetVC8WjFkhpPhtpbDM4Vw7r9m Monero (XMR): 4ACL8AGrEo5hAir8A9CeVrW8pEauWvnp1WnSDZxW7tziCDLhZAGsgzhRQABDnFy8yuM9fWJDviJPHKRjV4FWt19CJZN9D4n

Multimodal Machine Learning | Introduction | Part 1 | CVPR 2022 Tutorial

If you have any copyright issues on video, please send us an email at khawar512@gmail.com Top CV and PR Conferences: Publication h5-index h5-median 1. IEEE/CVF Conference on Computer Vision and Pattern Recognition 356 583 2. European Conference on Computer Vision 197 342 3. IEEE/CVF International Conference on Computer Vision 184 311 4. IEEE Transactions on Pattern Analysis and Machine Intelligence 149 275 5. IEEE Transactions on Image Processing 123 187 6. Pattern Recognition 99 141 7. IEEE/CVF Computer Society Conference on Computer Vision and Pattern Recognition Workshops (CVPRW) 89 154 8. Medical Image Analysis 76 149 9. International Journal of Computer Vision 72 173 10. British Machine Vision Conference (BMVC) 66 102 11. Pattern Recognition Letters 66 93 12. IEEE/CVF Winter Conference on Applications of Computer Vision (WACV) 62 121 13. IEEE International Conference on Image Processing (ICIP) 60 89 14. IEEE/CVF International Conference on Computer Vision Workshops (ICCVW) 57 83 15. Computer Vision and Image Understanding 52 91 16. Journal of Visual Communication and Image Representation 47 64 17. International Conference on 3D Vision (3DV) 44 89 18. International Conference on Pattern Recognition 43 78 19. Asian Conference on Computer Vision (ACCV) 43 69 20. IEEE International Conference on Automatic Face & Gesture Recognition 42 66 Top Papers at CVPR Deep Residual Learning for Image Recognition. Densely Connected Convolutional Networks. You Only Look Once: Unified, Real-Time Object Detection. Rethinking the Inception Architecture for Computer Vision. Image-to-Image Translation with Conditional Adversarial Networks. YOLO9000: Better, Faster, Stronger. Feature Pyramid Networks for Object Detection. Squeeze-and-Excitation Networks Photo-Realistic Single Image Super-Resolution Using a Generative Adversarial Network. Xception: Deep Learning with Depthwise Separable Convolutions. MobileNetV2: Inverted Residuals and Linear Bottlenecks The Cityscapes Dataset for Semantic Urban Scene Understanding. Pyramid Scene Parsing Network. PointNet: Deep Learning on Point Sets for 3D Classification and Segmentation. Aggregated Residual Transformations for Deep Neural Networks. Learning Deep Features for Discriminative Localization. Accurate Image Super-Resolution Using Very Deep Convolutional Networks. Realtime Multi-person 2D Pose Estimation Using Part Affinity Fields. Non-local Neural Networks Quo Vadis, Action Recognition? A New Model and the Kinetics Dataset.

Multimodal Machine Learning | Transference | Part 6 | CVPR 2022 Tutorial

If you have any copyright issues on video, please send us an email at khawar512@gmail.com Top CV and PR Conferences: Publication h5-index h5-median 1. IEEE/CVF Conference on Computer Vision and Pattern Recognition 356 583 2. European Conference on Computer Vision 197 342 3. IEEE/CVF International Conference on Computer Vision 184 311 4. IEEE Transactions on Pattern Analysis and Machine Intelligence 149 275 5. IEEE Transactions on Image Processing 123 187 6. Pattern Recognition 99 141 7. IEEE/CVF Computer Society Conference on Computer Vision and Pattern Recognition Workshops (CVPRW) 89 154 8. Medical Image Analysis 76 149 9. International Journal of Computer Vision 72 173 10. British Machine Vision Conference (BMVC) 66 102 11. Pattern Recognition Letters 66 93 12. IEEE/CVF Winter Conference on Applications of Computer Vision (WACV) 62 121 13. IEEE International Conference on Image Processing (ICIP) 60 89 14. IEEE/CVF International Conference on Computer Vision Workshops (ICCVW) 57 83 15. Computer Vision and Image Understanding 52 91 16. Journal of Visual Communication and Image Representation 47 64 17. International Conference on 3D Vision (3DV) 44 89 18. International Conference on Pattern Recognition 43 78 19. Asian Conference on Computer Vision (ACCV) 43 69 20. IEEE International Conference on Automatic Face & Gesture Recognition 42 66 Top Papers at CVPR Deep Residual Learning for Image Recognition. Densely Connected Convolutional Networks. You Only Look Once: Unified, Real-Time Object Detection. Rethinking the Inception Architecture for Computer Vision. Image-to-Image Translation with Conditional Adversarial Networks. YOLO9000: Better, Faster, Stronger. Feature Pyramid Networks for Object Detection. Squeeze-and-Excitation Networks Photo-Realistic Single Image Super-Resolution Using a Generative Adversarial Network. Xception: Deep Learning with Depthwise Separable Convolutions. MobileNetV2: Inverted Residuals and Linear Bottlenecks The Cityscapes Dataset for Semantic Urban Scene Understanding. Pyramid Scene Parsing Network. PointNet: Deep Learning on Point Sets for 3D Classification and Segmentation. Aggregated Residual Transformations for Deep Neural Networks. Learning Deep Features for Discriminative Localization. Accurate Image Super-Resolution Using Very Deep Convolutional Networks. Realtime Multi-person 2D Pose Estimation Using Part Affinity Fields. Non-local Neural Networks Quo Vadis, Action Recognition? A New Model and the Kinetics Dataset.

Multimodal Machine Learning | Quantification | Part 7 | CVPR 2022 Tutorial

If you have any copyright issues on video, please send us an email at khawar512@gmail.com Top CV and PR Conferences: Publication h5-index h5-median 1. IEEE/CVF Conference on Computer Vision and Pattern Recognition 356 583 2. European Conference on Computer Vision 197 342 3. IEEE/CVF International Conference on Computer Vision 184 311 4. IEEE Transactions on Pattern Analysis and Machine Intelligence 149 275 5. IEEE Transactions on Image Processing 123 187 6. Pattern Recognition 99 141 7. IEEE/CVF Computer Society Conference on Computer Vision and Pattern Recognition Workshops (CVPRW) 89 154 8. Medical Image Analysis 76 149 9. International Journal of Computer Vision 72 173 10. British Machine Vision Conference (BMVC) 66 102 11. Pattern Recognition Letters 66 93 12. IEEE/CVF Winter Conference on Applications of Computer Vision (WACV) 62 121 13. IEEE International Conference on Image Processing (ICIP) 60 89 14. IEEE/CVF International Conference on Computer Vision Workshops (ICCVW) 57 83 15. Computer Vision and Image Understanding 52 91 16. Journal of Visual Communication and Image Representation 47 64 17. International Conference on 3D Vision (3DV) 44 89 18. International Conference on Pattern Recognition 43 78 19. Asian Conference on Computer Vision (ACCV) 43 69 20. IEEE International Conference on Automatic Face & Gesture Recognition 42 66 Top Papers at CVPR Deep Residual Learning for Image Recognition. Densely Connected Convolutional Networks. You Only Look Once: Unified, Real-Time Object Detection. Rethinking the Inception Architecture for Computer Vision. Image-to-Image Translation with Conditional Adversarial Networks. YOLO9000: Better, Faster, Stronger. Feature Pyramid Networks for Object Detection. Squeeze-and-Excitation Networks Photo-Realistic Single Image Super-Resolution Using a Generative Adversarial Network. Xception: Deep Learning with Depthwise Separable Convolutions. MobileNetV2: Inverted Residuals and Linear Bottlenecks The Cityscapes Dataset for Semantic Urban Scene Understanding. Pyramid Scene Parsing Network. PointNet: Deep Learning on Point Sets for 3D Classification and Segmentation. Aggregated Residual Transformations for Deep Neural Networks. Learning Deep Features for Discriminative Localization. Accurate Image Super-Resolution Using Very Deep Convolutional Networks. Realtime Multi-person 2D Pose Estimation Using Part Affinity Fields. Non-local Neural Networks Quo Vadis, Action Recognition? A New Model and the Kinetics Dataset.

Multimodal Machine Learning | Alignment | Part 3 | CVPR 2022 Tutorial

If you have any copyright issues on video, please send us an email at khawar512@gmail.com Top CV and PR Conferences: Publication h5-index h5-median 1. IEEE/CVF Conference on Computer Vision and Pattern Recognition 356 583 2. European Conference on Computer Vision 197 342 3. IEEE/CVF International Conference on Computer Vision 184 311 4. IEEE Transactions on Pattern Analysis and Machine Intelligence 149 275 5. IEEE Transactions on Image Processing 123 187 6. Pattern Recognition 99 141 7. IEEE/CVF Computer Society Conference on Computer Vision and Pattern Recognition Workshops (CVPRW) 89 154 8. Medical Image Analysis 76 149 9. International Journal of Computer Vision 72 173 10. British Machine Vision Conference (BMVC) 66 102 11. Pattern Recognition Letters 66 93 12. IEEE/CVF Winter Conference on Applications of Computer Vision (WACV) 62 121 13. IEEE International Conference on Image Processing (ICIP) 60 89 14. IEEE/CVF International Conference on Computer Vision Workshops (ICCVW) 57 83 15. Computer Vision and Image Understanding 52 91 16. Journal of Visual Communication and Image Representation 47 64 17. International Conference on 3D Vision (3DV) 44 89 18. International Conference on Pattern Recognition 43 78 19. Asian Conference on Computer Vision (ACCV) 43 69 20. IEEE International Conference on Automatic Face & Gesture Recognition 42 66 Top Papers at CVPR Deep Residual Learning for Image Recognition. Densely Connected Convolutional Networks. You Only Look Once: Unified, Real-Time Object Detection. Rethinking the Inception Architecture for Computer Vision. Image-to-Image Translation with Conditional Adversarial Networks. YOLO9000: Better, Faster, Stronger. Feature Pyramid Networks for Object Detection. Squeeze-and-Excitation Networks Photo-Realistic Single Image Super-Resolution Using a Generative Adversarial Network. Xception: Deep Learning with Depthwise Separable Convolutions. MobileNetV2: Inverted Residuals and Linear Bottlenecks The Cityscapes Dataset for Semantic Urban Scene Understanding. Pyramid Scene Parsing Network. PointNet: Deep Learning on Point Sets for 3D Classification and Segmentation. Aggregated Residual Transformations for Deep Neural Networks. Learning Deep Features for Discriminative Localization. Accurate Image Super-Resolution Using Very Deep Convolutional Networks. Realtime Multi-person 2D Pose Estimation Using Part Affinity Fields. Non-local Neural Networks Quo Vadis, Action Recognition? A New Model and the Kinetics Dataset.

Multimodal Machine Learning | Reasoning | Part 4 | CVPR 2022 Tutorial

If you have any copyright issues on video, please send us an email at khawar512@gmail.com Top CV and PR Conferences: Publication h5-index h5-median 1. IEEE/CVF Conference on Computer Vision and Pattern Recognition 356 583 2. European Conference on Computer Vision 197 342 3. IEEE/CVF International Conference on Computer Vision 184 311 4. IEEE Transactions on Pattern Analysis and Machine Intelligence 149 275 5. IEEE Transactions on Image Processing 123 187 6. Pattern Recognition 99 141 7. IEEE/CVF Computer Society Conference on Computer Vision and Pattern Recognition Workshops (CVPRW) 89 154 8. Medical Image Analysis 76 149 9. International Journal of Computer Vision 72 173 10. British Machine Vision Conference (BMVC) 66 102 11. Pattern Recognition Letters 66 93 12. IEEE/CVF Winter Conference on Applications of Computer Vision (WACV) 62 121 13. IEEE International Conference on Image Processing (ICIP) 60 89 14. IEEE/CVF International Conference on Computer Vision Workshops (ICCVW) 57 83 15. Computer Vision and Image Understanding 52 91 16. Journal of Visual Communication and Image Representation 47 64 17. International Conference on 3D Vision (3DV) 44 89 18. International Conference on Pattern Recognition 43 78 19. Asian Conference on Computer Vision (ACCV) 43 69 20. IEEE International Conference on Automatic Face & Gesture Recognition 42 66 Top Papers at CVPR Deep Residual Learning for Image Recognition. Densely Connected Convolutional Networks. You Only Look Once: Unified, Real-Time Object Detection. Rethinking the Inception Architecture for Computer Vision. Image-to-Image Translation with Conditional Adversarial Networks. YOLO9000: Better, Faster, Stronger. Feature Pyramid Networks for Object Detection. Squeeze-and-Excitation Networks Photo-Realistic Single Image Super-Resolution Using a Generative Adversarial Network. Xception: Deep Learning with Depthwise Separable Convolutions. MobileNetV2: Inverted Residuals and Linear Bottlenecks The Cityscapes Dataset for Semantic Urban Scene Understanding. Pyramid Scene Parsing Network. PointNet: Deep Learning on Point Sets for 3D Classification and Segmentation. Aggregated Residual Transformations for Deep Neural Networks. Learning Deep Features for Discriminative Localization. Accurate Image Super-Resolution Using Very Deep Convolutional Networks. Realtime Multi-person 2D Pose Estimation Using Part Affinity Fields. Non-local Neural Networks Quo Vadis, Action Recognition? A New Model and the Kinetics Dataset.

Multimodal Machine Learning | Generation | Part 5 | CVPR 2022 Tutorial

If you have any copyright issues on video, please send us an email at khawar512@gmail.com Top CV and PR Conferences: Publication h5-index h5-median 1. IEEE/CVF Conference on Computer Vision and Pattern Recognition 356 583 2. European Conference on Computer Vision 197 342 3. IEEE/CVF International Conference on Computer Vision 184 311 4. IEEE Transactions on Pattern Analysis and Machine Intelligence 149 275 5. IEEE Transactions on Image Processing 123 187 6. Pattern Recognition 99 141 7. IEEE/CVF Computer Society Conference on Computer Vision and Pattern Recognition Workshops (CVPRW) 89 154 8. Medical Image Analysis 76 149 9. International Journal of Computer Vision 72 173 10. British Machine Vision Conference (BMVC) 66 102 11. Pattern Recognition Letters 66 93 12. IEEE/CVF Winter Conference on Applications of Computer Vision (WACV) 62 121 13. IEEE International Conference on Image Processing (ICIP) 60 89 14. IEEE/CVF International Conference on Computer Vision Workshops (ICCVW) 57 83 15. Computer Vision and Image Understanding 52 91 16. Journal of Visual Communication and Image Representation 47 64 17. International Conference on 3D Vision (3DV) 44 89 18. International Conference on Pattern Recognition 43 78 19. Asian Conference on Computer Vision (ACCV) 43 69 20. IEEE International Conference on Automatic Face & Gesture Recognition 42 66 Top Papers at CVPR Deep Residual Learning for Image Recognition. Densely Connected Convolutional Networks. You Only Look Once: Unified, Real-Time Object Detection. Rethinking the Inception Architecture for Computer Vision. Image-to-Image Translation with Conditional Adversarial Networks. YOLO9000: Better, Faster, Stronger. Feature Pyramid Networks for Object Detection. Squeeze-and-Excitation Networks Photo-Realistic Single Image Super-Resolution Using a Generative Adversarial Network. Xception: Deep Learning with Depthwise Separable Convolutions. MobileNetV2: Inverted Residuals and Linear Bottlenecks The Cityscapes Dataset for Semantic Urban Scene Understanding. Pyramid Scene Parsing Network. PointNet: Deep Learning on Point Sets for 3D Classification and Segmentation. Aggregated Residual Transformations for Deep Neural Networks. Learning Deep Features for Discriminative Localization. Accurate Image Super-Resolution Using Very Deep Convolutional Networks. Realtime Multi-person 2D Pose Estimation Using Part Affinity Fields. Non-local Neural Networks Quo Vadis, Action Recognition? A New Model and the Kinetics Dataset.

Multimodal Machine Learning | Representation | Part 2 | CVPR 2022 Tutorial

If you have any copyright issues on video, please send us an email at khawar512@gmail.com Top CV and PR Conferences: Publication h5-index h5-median 1. IEEE/CVF Conference on Computer Vision and Pattern Recognition 356 583 2. European Conference on Computer Vision 197 342 3. IEEE/CVF International Conference on Computer Vision 184 311 4. IEEE Transactions on Pattern Analysis and Machine Intelligence 149 275 5. IEEE Transactions on Image Processing 123 187 6. Pattern Recognition 99 141 7. IEEE/CVF Computer Society Conference on Computer Vision and Pattern Recognition Workshops (CVPRW) 89 154 8. Medical Image Analysis 76 149 9. International Journal of Computer Vision 72 173 10. British Machine Vision Conference (BMVC) 66 102 11. Pattern Recognition Letters 66 93 12. IEEE/CVF Winter Conference on Applications of Computer Vision (WACV) 62 121 13. IEEE International Conference on Image Processing (ICIP) 60 89 14. IEEE/CVF International Conference on Computer Vision Workshops (ICCVW) 57 83 15. Computer Vision and Image Understanding 52 91 16. Journal of Visual Communication and Image Representation 47 64 17. International Conference on 3D Vision (3DV) 44 89 18. International Conference on Pattern Recognition 43 78 19. Asian Conference on Computer Vision (ACCV) 43 69 20. IEEE International Conference on Automatic Face & Gesture Recognition 42 66 Top Papers at CVPR Deep Residual Learning for Image Recognition. Densely Connected Convolutional Networks. You Only Look Once: Unified, Real-Time Object Detection. Rethinking the Inception Architecture for Computer Vision. Image-to-Image Translation with Conditional Adversarial Networks. YOLO9000: Better, Faster, Stronger. Feature Pyramid Networks for Object Detection. Squeeze-and-Excitation Networks Photo-Realistic Single Image Super-Resolution Using a Generative Adversarial Network. Xception: Deep Learning with Depthwise Separable Convolutions. MobileNetV2: Inverted Residuals and Linear Bottlenecks The Cityscapes Dataset for Semantic Urban Scene Understanding. Pyramid Scene Parsing Network. PointNet: Deep Learning on Point Sets for 3D Classification and Segmentation. Aggregated Residual Transformations for Deep Neural Networks. Learning Deep Features for Discriminative Localization. Accurate Image Super-Resolution Using Very Deep Convolutional Networks. Realtime Multi-person 2D Pose Estimation Using Part Affinity Fields. Non-local Neural Networks Quo Vadis, Action Recognition? A New Model and the Kinetics Dataset.

[ML News] Text-to-Image models are taking over! (Imagen, DALL-E 2, Midjourney, CogView 2 & more)

#mlnews #dalle #imagen All things text-to-image models like DALL-E and Imagen! OUTLINE: 0:00 - Intro 0:30 - Imagen: Google's Text-to-Image Diffusion Model 7:15 - Unified I/O by AllenAI 9:40 - CogView2 is Open-Source 11:05 - Google bans DeepFakes from Colab 13:05 - DALL-E generates real Cosmopolitan cover 15:45 - DALL-E tips & tricks 17:00 - Midjourney moves to Open Beta 17:50 - DALLE-mini is not Crayon 19:00 - Deep Learning Resources References: Imagen: Google's Text-to-Image Diffusion Model https://ift.tt/yACYd6U https://ift.tt/M1uheYa Unified I/O by AllenAI https://ift.tt/ow0pdl4 https://ift.tt/7XLpgKV CogView2 is Open-Source https://ift.tt/J0r2bUf file:///Users/yk/Downloads/big.1.pdf https://ift.tt/LxoTpZz https://ift.tt/9Z4By7v Google bans DeepFakes from Colab https://ift.tt/MvzqgAH DALL-E generates real Cosmopolitan cover https://ift.tt/MtWhiRz https://ift.tt/6z1twpd DALL-E tips & tricks https://twitter.com/GuyP/status/1544710725708513280?s=09&t=c3NpErPx80INQVeaWkIqIg&utm_source=pocket_mylist https://twitter.com/GuyP/status/1552681939806691329?s=09&t=LV2ChcukUziXfvfNK-sY0A&utm_source=pocket_mylist https://twitter.com/GuyP/status/1547234780001042432 https://ift.tt/SrLaFKA Midjourney moves to Open Beta https://twitter.com/midjourney?lang=en https://twitter.com/search?q=%23midjourney&f=image DALLE-mini is not Crayon https://ift.tt/foVMAvU Deep Learning Resources https://ift.tt/ZhpDCEF https://ift.tt/BIp2DLV https://ift.tt/pa3qFg9 Links: Homepage: https://ykilcher.com Merch: https://ift.tt/eFI6pq3 YouTube: https://www.youtube.com/c/yannickilcher Twitter: https://twitter.com/ykilcher Discord: https://ift.tt/GCmnFay LinkedIn: https://ift.tt/c7paHkt If you want to support me, the best thing to do is to share out the content :) If you want to support me financially (completely optional and voluntary, but a lot of people have asked for this): SubscribeStar: https://ift.tt/velGS6h Patreon: https://ift.tt/hGKAgwY Bitcoin (BTC): bc1q49lsw3q325tr58ygf8sudx2dqfguclvngvy2cq Ethereum (ETH): 0x7ad3513E3B8f66799f507Aa7874b1B0eBC7F85e2 Litecoin (LTC): LQW2TRyKYetVC8WjFkhpPhtpbDM4Vw7r9m Monero (XMR): 4ACL8AGrEo5hAir8A9CeVrW8pEauWvnp1WnSDZxW7tziCDLhZAGsgzhRQABDnFy8yuM9fWJDviJPHKRjV4FWt19CJZN9D4n

Complete Data Analytics | Become a Data Analyst with @AI QUEST Python, SQL, PowerBi, Tableau, Excel

✅ Become a Data Analyst (Python, Excel, Tableau, PowerBi, GDS): https://deluxe-airmail-22b.notion.site/Become-a-Data-Analyst-with-AiQuest-51ace55cc048492ca69a1916e0871b50 ✅ List of all Paid Courses: https://allmylinks.com/studymart-paid-courses ✅ Must Join the Facebook Group: https://facebook.com/groups/StudyMart ✅ To Enroll in Paid Courses, Contact: +8801704265972 (Sohan Khan) ✅ Another Facebook Group: https://facebook.com/groups/aiQuest ✅ Let's Subscribe to AI QUEST: https://www.youtube.com/aiquest?sub_confirmation=1 Our Paid Courses: ✅ List of all Paid Courses: https://allmylinks.com/studymart-paid-courses ✅ SQL For Data Science: https://be-data-engineer.notion.site/be-data-engineer/SQL-for-Data-Science-da60b6a0a0fc430f8e3d43c382ce649a ✅ Data Science & Machine Learning with Python: https://drive.google.com/file/d/16V-ic9wnHN6nTigoAe7cmkQwZfYMQ1JD ✅ Big Data Engineer: https://be-data-engineer.notion.site/be-data-engineer/Become-a-Big-Data-Engineer-06127136005044a1b7bd8a6c6e17595f ✅ Deep Learning & NLP with Python: https://drive.google.com/file/d/1K32UCjdzyYQ53XYfEjdOp8PRN6Dzv3W4 ✅ Become a Data Analyst (Excel, Tableau, PowerBi, GDS): https://deluxe-airmail-22b.notion.site/Become-a-Data-Analyst-with-AiQuest-51ace55cc048492ca69a1916e0871b50 ✅ To Enroll in Paid Courses, Contact: +8801704265972 (Sohan Khan) You can join me: ✅ Let's Subscribe to AI QUEST: https://www.youtube.com/aiquest?sub_confirmation=1 ✅ Follow Me: https://www.facebook.com/MrArgon28 ✅ Follow Facebook: https://facebook.com/StudyMart.org ✅ Follow me on Page: https://facebook.com/shakil.RashedulAlam ✅Follow Linkedin: https://www.linkedin.com/company/study-mart ✅Patreon: https://patreon.com/StudyMart ✅ Vist Website: https://www.aiquest.org Others Playlist: ✅ 60 Days of Python: https://www.youtube.com/watch?v=FZmPnTVOAR4&list=PLKdU0fuY4OFf7qj4eoBtvALAB_Ml2rN0V ✅ Python & Machine Learning Full Playlist: https://www.youtube.com/watch?v=A3FKSsYy0Zg&list=PLKdU0fuY4OFcot0zyVbM1-zKf_eCUK4zQ ✅ MongoDB NoSql Database: https://www.youtube.com/watch?v=nuJ6qoBcZaw&list=PLKdU0fuY4OFe5tIAh3FB8avnQBD5FFXvE ✅ R Programming for Data Science: https://www.youtube.com/watch?v=-SZ_Ph4HuTc&list=PLKdU0fuY4OFdcvSMgwilt99n81IhhaHSX ✅ Learn Deep Learning Course: https://www.youtube.com/watch?v=BbckQ-bLLG8&list=PLKdU0fuY4OFdFUCFcUp-7VD4bLXr50hgb ✅ Learn Machine Learning Full Course: https://www.youtube.com/watch?v=xYMHT4uMOiE&list=PLKdU0fuY4OFfWY36nDJDlI26jXwInSm8f ✅ Learn Advance Excel for Data Science: https://www.youtube.com/watch?v=FFV_YmDxgj0&list=PLKdU0fuY4OFcx1_w_MhD4c0vRvP_8jYW9 ✅ Feature Engineering in Machine Learning: https://www.youtube.com/watch?v=Y1O_3TuVs_8&list=PLKdU0fuY4OFfUUWMHeqX5XxXYhUZnaXUe ✅ Data Science Bangla Playlist: https://www.youtube.com/watch?v=9BtpCvUtKL8&list=PLKdU0fuY4OFd2SIraaUtJ4nJ9F8o48kYT ✅ C Bangla Tutorial Playlist: https://www.youtube.com/watch?v=rpB6QRkwJd0&list=PLKdU0fuY4OFct8iFqcxhJcd3wjjK60LgO ✅ Linux Bangla Tutorial Playlist: https://www.youtube.com/watch?v=JowAv7hGVJg&list=PLKdU0fuY4OFeq7C9AjjceGFPzFUH0OoMH ✅ Prolog Bangla Tutorial Series: https://www.youtube.com/watch?v=Uzv9aj2aPj0&list=PLKdU0fuY4OFeLM-IEmZYLe3eHEUlSGru5 Tags: data analysis,data analytics,data science,sql,python,data analyst,data analysis using python,python for data analysis,powerbi,tableau,database,complete data analytics,complete data science,python tutorial,python data analysis,data,ai,machine learning,database engineer roadmap,sql for data analysis,sql for data science, data analysis,data analytics,data science,sql,python,data analyst,data analysis using python,python for data analysis,powerbi,tableau,database,complete data analytics,complete data science,python tutorial,python data analysis,data,ai,machine learning,database engineer roadmap,sql for data analysis,sql for data science,data analysis bangla,bangla course,paid,data analytics for beginners,data analyst job,how to become a data analyst

Regression Analysis | Regression Analysis Statistics | Regression Analysis Explained | Simplilearn

In this video we are going to cover how regression analysis perform by SVM algorithm using Olympic 2022 dataset. This video will help you to understand what is machine learning, what is supervised learning, types of supervised learning - Classification and Regression, What is regression analysis , why do we use regression analysis, Popular algorithms in regression analysis, Advantages and Disadvantages of different regression analysis models, Applications of regression analysis, hands on lab using SVM algorithm and job opportunity. Below are the topics we are going to discuss in this tutorial. 00:00 What is Machine Learning 02:38 What is Supervised Learning 04:50 What is Regression Analysis 06:45 Why do we use Regression Analysis 09:00 Popular algorithms in Regression Analysis 10:59 Advantages and Disadvantages of different regression analysis models 12:24 Applications of regression analysis 14:08Hands on lab using SVM algorithm 49:54 job opportunity ✅Subscribe to our Channel to learn more about the top Technologies: https://bit.ly/2VT4WtH ⏩ Check out the Machine Learning tutorial videos: https://bit.ly/3fFR4f4 #regressionAnalysis #linearRegression #logisticRegression #statistics #datascience #datasciencetutorial #datascienceforbeginners #datasciencewithr #datasciencetutorialforbeginners #datasciencecourse Dataset Link - https://drive.google.com/drive/folders/1aJeMxasLbOL9atJJ1gDsonjmsz8H5Ece?usp=sharing About Machine Learning Certification Course: Explore this Machine Learning certification course to understand cutting-edge concepts in machine learning, an exciting branch of Artificial Intelligence. This Machine Learning online training will provide you the skills needed to become a successful Machine Learning Engineer today. Machine Learning Course Overview: This Machine Learning course offers an in-depth overview of Machine Learning topics including working with real-time data, developing algorithms using supervised & unsupervised learning, regression, classification, and time series modeling. Machine Learning Training Key Features: ✅ 100% Money Back Guarantee ✅ Gain expertise with 25+ hands-on exercises ✅ 4 real-life industry projects with integrated labs ✅ Dedicated mentoring sessions from industry experts ✅ 58 hours of Applied Learning Benefits of Machine Learning Course: The Machine Learning market is expected to reach USD $8.81 Billion by 2022, at a growth rate of 44.1-percent, indicating the increased adoption of Machine Learning among companies. By 2020, the demand for Machine Learning engineers is expected to grow by 60-percent. Eligibility of Machine Learning Course: The Machine Learning certification online course is well-suited for participants at the intermediate level including, analytics managers, business analysts, information architects, developers looking to become data scientists, and graduates seeking a career in Data Science and Machine Learning. Pre-requisites of Machine Learning Course: This Machine Learning course requires an understanding of basic statistics and mathematics at the college level. Familiarity with Python programming is also beneficial. You should understand these fundamental courses including Python for Data Science, Math Refresher, and Statistics Essential for Data Science, before getting into the Machine Learning online course. How do I become a Machine Learning Engineer? This course will give you a complete overview of Machine Learning methodologies, enough to prepare you to excel in your next role as a Machine Learning Engineer. You will earn Simplilearn’s Machine Learning certification that will attest to your new skills and on-the-job expertise. 👉Learn more at: https://www.simplilearn.com/pgp-ai-machine-learning-certification-training-course?utm_campaign=MachineLearningFC&utm_medium=Description&utm_source=youtube Get the Simplilearn app: https://simpli.app.link/OlbFAhqMqgb For more information about Simplilearn’s courses, visit: - Facebook: https://www.facebook.com/Simplilearn - Twitter: https://twitter.com/simplilearn - LinkedIn: https://www.linkedin.com/company/simplilearn/ - Website: https://www.simplilearn.com - Instagram: https://www.instagram.com/simplilearn_elearning - Telegram Mobile: https://t.me/simplilearnupdates - Telegram Desktop: https://web.telegram.org/#/im?p=@simplilearnupdates Get the Simplilearn app: https://simpli.app.link/OlbFAhqMqgb

TensorFlow Serving performance optimization

Wei Wei, Developer Advocate at Google, shares general principles and best practices to improve TensorFlow Serving performance. He discusses how to improve the latency for API surfaces, batching, and more parameters that you can tune. Resources: TensorFlow Serving performance guide → https://goo.gle/3zW168E Profile Inference Requests with TensorBoard → https://goo.gle/3zWjluJ TensorFlow Serving batching configuration → https://goo.gle/3xT2SVz TensorFlow Serving SavedModel Warmup → https://goo.gle/3ygfIhT XLA homepage → https://goo.gle/3zY01gw How to make TensorFlow models run faster on GPUs (with XLA) → https://goo.gle/3OAB8LR How OpenX Trains and Serves for a Million Queries per Second in under 15 Milliseconds → https://goo.gle/3NdAOSd ResNet complete example → https://goo.gle/3zU1PHs Deploying Production ML Models with TensorFlow Serving playlist → Subscribe to TensorFlow → https://goo.gle/TensorFlow #TensorFlow