Free artificial intelligence and machine learning video tutorial resource: 2024

Friday, April 26, 2024

COE | STEFAN LAUBER - 4IR & AI

Predictive Maintenance: AI Prevents Missile System Failures! Part 1 #ai #viral #trending

Predictive Maintenance: AI Prevents Missile System Failures! Part 1 #ai #viral #trending Keeping missiles mission-ready is critical for national defense. In this video, we'll explore how Artificial Intelligence (AI) is revolutionizing predictive maintenance for missile systems. Why Predictive Maintenance is Crucial for Missiles: High-Tech Systems: Modern missiles are complex systems with numerous components susceptible to wear and tear. Mission-Critical Performance: Missile failures during deployment can have catastrophic consequences. Preventive Maintenance vs. Reactive Repairs: Predicting and addressing potential issues before they escalate is crucial for maintaining readiness. How AI Enables Predictive Maintenance for Missiles: Sensor Data Analysis: AI can analyze data from various sensors on missiles, identifying patterns and anomalies indicative of potential problems. Machine Learning Algorithms: AI algorithms learn from historical maintenance data and sensor readings to predict future component failures. Proactive Maintenance Scheduling: Based on AI predictions, maintenance schedules can be optimized, addressing issues before they impact functionality. Real-time Health Monitoring: AI can continuously monitor missile systems, enabling early detection of problems and faster response times. Benefits of AI-powered Predictive Maintenance for Missiles: Improved System Availability: Predictive maintenance reduces downtime and ensures missiles are ready for deployment when needed. Enhanced Safety and Reliability: Proactive identification of potential failures minimizes the risk of in-flight malfunctions. Reduced Maintenance Costs: Focusing on targeted maintenance based on AI predictions can be more efficient than routine overhauls. Optimized Resource Allocation: Maintenance resources can be prioritized based on AI predictions, ensuring critical issues are addressed first. Challenges and Considerations of AI-powered Predictive Maintenance: Data Quality and Integration: The effectiveness of AI relies on access to high-quality, comprehensive sensor data from missiles and maintenance records. Explainability of AI Predictions: Understanding how AI reaches conclusions about potential failures is crucial for building trust with human maintenance personnel. Integration with Existing Systems: Seamless integration of AI-powered predictive maintenance systems with existing maintenance infrastructure is necessary. The Future of AI and Predictive Maintenance for Missiles: Development of Explainable AI (XAI) for Maintenance Prediction: Making AI's reasoning more transparent to enhance collaboration and trust with human technicians. Advanced Sensor Technologies: Integration of new sensor technologies can provide AI with even richer data for more accurate predictions. Standardization of Data Formats: Developing standardized data formats across different missile systems can facilitate better data integration and analysis. By leveraging AI, we can create a more proactive and efficient approach to missile maintenance. However, ensuring data quality, fostering trust in AI predictions, and integrating with existing systems are crucial for successful implementation. #AI #PredictiveMaintenance #MissileSystems #Maintenance #Reliability #Safety #CostSavings #ResourceAllocation #SensorDataAnalysis #MachineLearning #RealTimeMonitoring #ExplainableAI #DataQuality #Integration #FutureofMaintenance #DefenseTechnology artificial intelligence, predictive maintenance, missile systems, maintenance, reliability, safety, cost savings, resource allocation, sensor data analysis, machine learning, real-time monitoring, explainable AI, data quality, integration, future of maintenance, defense technology #artificialintelligence #ai #machinelearning #deeplearning #dataanalytics #bigdata #futureofwork #futurism #algorithms #automation #aiingujarat #educational #informative #technology #trends #future #disruption #opportunities #challenges #impact #society #humanity #vlog #music #funny #tutorial #challenge #love #gaming #comedy #art #life #cute #travel #fashion #beauty #dance #food #pets #motivation #fitness #trending #gamer #minecraft #fortnite #gta #cod #apexlegends #pubg #valorant #leagueoflegends #roblox #makeup #skincare #hairstyle #beautyhacks #hairstyletutorial #skincaretips #makeuproutine #nails #tech #gadget #review #unboxing #iphone #android #apple #samsung #smartphone #laptop #viral #ai #mobile #movie #shorts #song #game #aiinindia #viral #video #viralvideo #shorts #youtubeshorts #youtube #youtuber #ai #trending #bestvideo #funny #tekthrill www.youtube.com https://youtube.com/@TEKTHRILL?si=rl1JYFFIjD5oqpJ3 Tekthrill The AI Tekthrill Future of AI Keyur Kuvadiya Youtube

Predictive Maintenance: AI Prevents Missile System Failures! Part 3 #ai #viral #trending

Predictive Maintenance: AI Prevents Missile System Failures! Part 3 #ai #viral #trending Keeping missiles mission-ready is critical for national defense. In this video, we'll explore how Artificial Intelligence (AI) is revolutionizing predictive maintenance for missile systems. Why Predictive Maintenance is Crucial for Missiles: High-Tech Systems: Modern missiles are complex systems with numerous components susceptible to wear and tear. Mission-Critical Performance: Missile failures during deployment can have catastrophic consequences. Preventive Maintenance vs. Reactive Repairs: Predicting and addressing potential issues before they escalate is crucial for maintaining readiness. How AI Enables Predictive Maintenance for Missiles: Sensor Data Analysis: AI can analyze data from various sensors on missiles, identifying patterns and anomalies indicative of potential problems. Machine Learning Algorithms: AI algorithms learn from historical maintenance data and sensor readings to predict future component failures. Proactive Maintenance Scheduling: Based on AI predictions, maintenance schedules can be optimized, addressing issues before they impact functionality. Real-time Health Monitoring: AI can continuously monitor missile systems, enabling early detection of problems and faster response times. Benefits of AI-powered Predictive Maintenance for Missiles: Improved System Availability: Predictive maintenance reduces downtime and ensures missiles are ready for deployment when needed. Enhanced Safety and Reliability: Proactive identification of potential failures minimizes the risk of in-flight malfunctions. Reduced Maintenance Costs: Focusing on targeted maintenance based on AI predictions can be more efficient than routine overhauls. Optimized Resource Allocation: Maintenance resources can be prioritized based on AI predictions, ensuring critical issues are addressed first. Challenges and Considerations of AI-powered Predictive Maintenance: Data Quality and Integration: The effectiveness of AI relies on access to high-quality, comprehensive sensor data from missiles and maintenance records. Explainability of AI Predictions: Understanding how AI reaches conclusions about potential failures is crucial for building trust with human maintenance personnel. Integration with Existing Systems: Seamless integration of AI-powered predictive maintenance systems with existing maintenance infrastructure is necessary. The Future of AI and Predictive Maintenance for Missiles: Development of Explainable AI (XAI) for Maintenance Prediction: Making AI's reasoning more transparent to enhance collaboration and trust with human technicians. Advanced Sensor Technologies: Integration of new sensor technologies can provide AI with even richer data for more accurate predictions. Standardization of Data Formats: Developing standardized data formats across different missile systems can facilitate better data integration and analysis. By leveraging AI, we can create a more proactive and efficient approach to missile maintenance. However, ensuring data quality, fostering trust in AI predictions, and integrating with existing systems are crucial for successful implementation. #AI #PredictiveMaintenance #MissileSystems #Maintenance #Reliability #Safety #CostSavings #ResourceAllocation #SensorDataAnalysis #MachineLearning #RealTimeMonitoring #ExplainableAI #DataQuality #Integration #FutureofMaintenance #DefenseTechnology artificial intelligence, predictive maintenance, missile systems, maintenance, reliability, safety, cost savings, resource allocation, sensor data analysis, machine learning, real-time monitoring, explainable AI, data quality, integration, future of maintenance, defense technology #artificialintelligence #ai #machinelearning #deeplearning #dataanalytics #bigdata #futureofwork #futurism #algorithms #automation #aiingujarat #educational #informative #technology #trends #future #disruption #opportunities #challenges #impact #society #humanity #vlog #music #funny #tutorial #challenge #love #gaming #comedy #art #life #cute #travel #fashion #beauty #dance #food #pets #motivation #fitness #trending #gamer #minecraft #fortnite #gta #cod #apexlegends #pubg #valorant #leagueoflegends #roblox #makeup #skincare #hairstyle #beautyhacks #hairstyletutorial #skincaretips #makeuproutine #nails #tech #gadget #review #unboxing #iphone #android #apple #samsung #smartphone #laptop #viral #ai #mobile #movie #shorts #song #game #aiinindia #viral #video #viralvideo #shorts #youtubeshorts #youtube #youtuber #ai #trending #bestvideo #funny #tekthrill www.youtube.com https://youtube.com/@TEKTHRILL?si=rl1JYFFIjD5oqpJ3 Tekthrill The AI Tekthrill Future of AI Keyur Kuvadiya Youtube

How Machine Learning/AI Traders Beats Retail Traders with Example Strategy for Beginners

In this video we will discuss how traders who use machine learning strategies will outperform the retail traders in future. We will also explain how to create a machine e learning strategy right from scratch. The entire code is only available for our Prometheus students and can be found in the Strategies and Code section https://www.quantprogram.com/store We are thinking of creating a course purely focussing on Machine Learning and AI based trading strategies. We will only launch it if there is substantial interest as it takes lot of work to create one. Let us know if you are interested through the link below https://www.quantprogram.com/MLCourseRegister Our Course's https://www.quantprogram.com/store Full Beginner Tutorial for Tradingview Pinecript: https://youtu.be/G4ErIBbUZOc RSI Strategy Backtested Pinescript: https://youtu.be/w1ETamJ8DcE Backtesting Pullback Strategy Pinecript: https://youtu.be/F_yGjiB0bro Stan Weinstein Strategy Pinecript code: https://youtu.be/Wodr4rCWzPw Create Stop Loss Take Profit Code: https://youtu.be/yP7qWD0JElo Creating Trailing stop Loss in Tradingview Pinescript: https://youtu.be/ZWyVF0fmGMs RSI divergence V4 Pinescript code: https://youtu.be/zCfMv_FxvME Donchian Breakout Pinescript Code: https://youtu.be/7fBlpT0YHpc Inside day Strategy Pinescript Code: https://youtu.be/_-QIv0KYnSM Bullish Engulfing Strategy Pinescript Code: https://youtu.be/JMEI9zbacbA https://www.quantprogram.com/RSI_Divergence_V5

#5 #machinelearning #datascience #python #mcqs #deeplearning #ai #pca #shorts #trending #ytshorts

#machinelearning #datascience #python Source Code: ============================== ============================== Channel Contents:------------- Full Stack AI Mastery: From Python to Expert Systems: https://www.youtube.com/playlist?list=PLdF3rLdF4ICQZWqrFYTutbuqHSc_swn7H Deep Learning: https://www.youtube.com/playlist?list=PLdF3rLdF4ICQgPC9q-fD7LKqiDSKBoGH6 Machine Learning Tutorials: https://www.youtube.com/watch?v=GnTIt3IFKEQ&list=PLdF3rLdF4ICTrOTMQ5XaUtHc-K0KGQzSS&pp=gAQBiAQB NLP Transfromer Projects: https://www.youtube.com/watch?v=cLtKAhaUqeo&list=PLdF3rLdF4ICRND3Urdm2nf6MM9ntkjvO6&pp=gAQBiAQB LangChain OpenAI Projects: https://www.youtube.com/watch?v=XmGtJG4ubqs&list=PLdF3rLdF4ICTwGLcd7FjqVurZe2OaWlz5&pp=gAQBiAQB Scikit-learn Tutorials: https://www.youtube.com/watch?v=NcVgJKaFecY&list=PLdF3rLdF4ICSDzmnqIueQDdyODJB8TaA0&pp=gAQBiAQB 100 Days Pandas: https://www.youtube.com/watch?v=U-6mZM8Ejc0&list=PLdF3rLdF4ICQGnskar9tqCuhi_tSCk40-&pp=gAQBiAQB Machine Leaning Projects: https://www.youtube.com/watch?v=eAgwvECLIRk&list=PLdF3rLdF4ICTDKN1VVTfAv35NR5mjK_hk&pp=gAQBiAQB NLP Projects: https://www.youtube.com/watch?v=hG8K5h2J-5g&list=PLdF3rLdF4ICQ4-fSEucMqoqMz1tEyjp9q&pp=gAQBiAQB Recommendation System Projects: https://www.youtube.com/watch?v=_R9Q_iuyvdc&list=PLdF3rLdF4ICTgEwDYcRAECQPnS8eynavM&pp=gAQBiAQB computer vision projects: https://www.youtube.com/watch?v=Ip3sjNGK7zU&list=PLdF3rLdF4ICQ92Su6Tg-S6tOuxO32NgWs&pp=gAQBiAQB 100 days mahine learning: https://www.youtube.com/watch?v=15zmcnX1Wts&list=PLdF3rLdF4ICQs8-3EzEEGOIIf6zKRWA6A&pp=gAQBiAQB Machine Learning Interview Preparation: OpenCV Tutorials: https://www.youtube.com/watch?v=gseWKGSvQrA&list=PLdF3rLdF4ICQG-RyfcOK3UgPP1XwKLexB&pp=gAQBiAQB 100 days computer vision: https://www.youtube.com/watch?v=4FBorEEinq4&list=PLdF3rLdF4ICSDGGZz6wj118qbVtQwgt7h&pp=gAQBiAQB Python Chatbot Development: https://www.youtube.com/watch?v=zktB8ceV7K0&list=PLdF3rLdF4ICQ3IeMsyl6ZI4NK45TPK1GJ&pp=gAQBiAQB Machine Learning Regression Projects: https://www.youtube.com/watch?v=5nl2JQzCUlg&list=PLdF3rLdF4ICTDXoDdeeyz6u9VGI-XggEK&pp=gAQBiAQB Python Advance Programs: https://www.youtube.com/watch?v=KS8j67rR6_M&list=PLdF3rLdF4ICRj-s_NsGmjxiZe4GKw4bgO&pp=gAQBiAQB python search engines developement: https://www.youtube.com/watch?v=9IULlMcQLE4&list=PLdF3rLdF4ICReR8yF6AFMPwgxyD1IoFMz&pp=gAQBiAQB Coviod-19 Machine Learning Projects: https://www.youtube.com/watch?v=AhbvQbc8f-s&list=PLdF3rLdF4ICQeWXTfln9Y9TQuzQBt97HB&pp=gAQBiAQB ================================ My Acounts Links: Facebook: https://web.facebook.com/dailyverbs.wordspresentation Github: https://github.com/account Linkdin: https://www.linkedin.com/in/noor-saeed-654a23263/?lipi=urn%3Ali%3Apage%3Ad_flagship3_feed%3BeidTfdQpSxSZXyUUejm5QQ%3D%3Dlipi=urn%3Ali%3Apage%3Anotifications_index_index%3Bfab7a03f-abe6-4798-af17-7239d91f7998 Kaggle: https://www.kaggle.com/noorsaeed

What is MLOps? | MLOps Explained in 15 Minutes | MLOps Tutorial | MLOps Training | Edureka

🔥MLOps Certification Training Course: https://www.edureka.co/mlops-certification-training-course In this video on "What is MLOps", you will be learning the core concepts of MLOps. MLOps (Machine Learning Operations) refers to the practice of streamlining and automating the process of building, deploying, and maintaining machine learning models in production environments. This video explains the concept of MLOps using an easy-to-understand example, highlighting the reasons why MLOps is necessary for organizations. It covers the essential components involved in the MLOps lifecycle, such as data management, model training, deployment, monitoring, and updates. By the end of the video, you will be provided with an MLOps Roadmap to kickstart your career in the domain of MLOps. The video is designed to provide a straightforward explanation of MLOps, making it accessible to both beginners and experienced professionals in the field of machine learning. ✅ 00:00 - Introduction to MLOps ✅ 01:20 - What Is MLOps? ✅ 03:02 - Example for MLOps ✅ 05:31 - Why do we need MLOps? ✅ 08:35 - Components of MLOps ✅ 11:53 - Roadmap for MLOps ✅Subscribe to our channel to get video updates. Hit the subscribe button above: https://goo.gl/6ohpTV 📝Feel free to share your comments below.📝 𝐄𝐝𝐮𝐫𝐞𝐤𝐚 𝐎𝐧𝐥𝐢𝐧𝐞 𝐓𝐫𝐚𝐢𝐧𝐢𝐧𝐠 𝐚𝐧𝐝 𝐂𝐞𝐫𝐭𝐢𝐟𝐢𝐜𝐚𝐭𝐢𝐨𝐧𝐬 🔵 DevOps Online Training: http://bit.ly/3VkBRUT 🌕 AWS Online Training: http://bit.ly/3ADYwDY 🔵 React Online Training: http://bit.ly/3Vc4yDw 🌕 Tableau Online Training: http://bit.ly/3guTe6J 🔵 Power BI Online Training: http://bit.ly/3VntjMY 🌕 Selenium Online Training: http://bit.ly/3EVDtis 🔵 PMP Online Training: http://bit.ly/3XugO44 🌕 Salesforce Online Training: http://bit.ly/3OsAXDH 🔵 Cybersecurity Online Training: http://bit.ly/3tXgw8t 🌕 Java Online Training: http://bit.ly/3tRxghg 🔵 Big Data Online Training: http://bit.ly/3EvUqP5 🌕 RPA Online Training: http://bit.ly/3GFHKYB 🔵 Python Online Training: http://bit.ly/3Oubt8M 🌕 Azure Online Training: http://bit.ly/3i4P85F 🔴 𝐄𝐝𝐮𝐫𝐞𝐤𝐚 𝐑𝐨𝐥𝐞-𝐁𝐚𝐬𝐞𝐝 𝐂𝐨𝐮𝐫𝐬𝐞𝐬 🔵 DevOps Engineer Masters Program: http://bit.ly/3Oud9PC 🌕 Cloud Architect Masters Program: http://bit.ly/3OvueZy 🔵 Data Scientist Masters Program: http://bit.ly/3tUAOiT 🌕 Big Data Architect Masters Program: http://bit.ly/3tTWT0V 🔵 Machine Learning Engineer Masters Program: http://bit.ly/3AEq4c4 🌕 Business Intelligence Masters Program: http://bit.ly/3UZPqJz 🔵 Python Developer Masters Program: http://bit.ly/3EV6kDv 🔴 𝐄𝐝𝐮𝐫𝐞𝐤𝐚 𝐔𝐧𝐢𝐯𝐞𝐫𝐬𝐢𝐭𝐲 𝐏𝐫𝐨𝐠𝐫𝐚𝐦𝐬 🔵 Post Graduate Program in DevOps with Purdue University: https://bit.ly/3Ov52lT 🌕 Advanced Certificate Program in Data Science with E&ICT Academy, IIT Guwahati: http://bit.ly/3V7ffrh 🔵 Advanced Certificate Program in Cloud Computing with E&ICT Academy, IIT Guwahati: https://bit.ly/43vmME8 📌𝐓𝐞𝐥𝐞𝐠𝐫𝐚𝐦: https://t.me/edurekaupdates 📌𝐓𝐰𝐢𝐭𝐭𝐞𝐫: https://twitter.com/edurekain 📌𝐋𝐢𝐧𝐤𝐞𝐝𝐈𝐧: https://www.linkedin.com/company/edureka 📌𝐈𝐧𝐬𝐭𝐚𝐠𝐫𝐚𝐦: https://www.instagram.com/edureka_learning/ 📌𝐅𝐚𝐜𝐞𝐛𝐨𝐨𝐤: https://www.facebook.com/edurekaIN/ 📌𝐒𝐥𝐢𝐝𝐞𝐒𝐡𝐚𝐫𝐞: https://www.slideshare.net/EdurekaIN 📌𝐂𝐚𝐬𝐭𝐛𝐨𝐱: https://castbox.fm/networks/505?country=IN 📌𝐌𝐞𝐞𝐭𝐮𝐩: https://www.meetup.com/edureka/ 📌𝐂𝐨𝐦𝐦𝐮𝐧𝐢𝐭𝐲: https://www.edureka.co/community/ - - - - - - - - - - - - - - What is MLOps? MLOps, also known as Machine Learning Operations, refers to the practices, procedures, and tools employed for optimizing the deployment, management, and scaling of machine learning models in operational settings. It amalgamates principles from DevOps and data engineering to ensure the effective progression, implementation, supervision, and sustenance of machine learning frameworks. The primary goal of MLOps is to mechanize and standardize the lifespan of machine learning models, empowering entities to furnish high-quality, reliable, robust, and scalable AI solutions. - - - - - - - - - - - - - - What are the different job roles available after MLOps Certification Course? After obtaining certification in MLOps, you may be qualified for a range of job roles. Some of the more specific job roles you may be qualified for include MLOps Engineer, MLOps Lead, Devops & ML Engineer , Associate Architect - MLOps ,MLOps Consultant - - - - - - - - - - - - - - Will I get placement assistance after completing this MLOps Training? To help you in this endeavor, we have added a resume builder tool in your LMS. Now, you will be able to create a winning resume in just 3 easy steps. You will have unlimited access to use these templates across different roles and designations. All you need to do is, log in to your LMS and click on the ""create your resume"" option. For more information, please write back to us at sales@edureka.in or call us at IND: 9606058406 / US: +18338555775 (toll-free).

Predictive Maintenance: AI Prevents Missile System Failures! Part 7 #ai #viral #trending

Predictive Maintenance: AI Prevents Missile System Failures! Part 7 #ai #viral #trending Keeping missiles mission-ready is critical for national defense. In this video, we'll explore how Artificial Intelligence (AI) is revolutionizing predictive maintenance for missile systems. Why Predictive Maintenance is Crucial for Missiles: High-Tech Systems: Modern missiles are complex systems with numerous components susceptible to wear and tear. Mission-Critical Performance: Missile failures during deployment can have catastrophic consequences. Preventive Maintenance vs. Reactive Repairs: Predicting and addressing potential issues before they escalate is crucial for maintaining readiness. How AI Enables Predictive Maintenance for Missiles: Sensor Data Analysis: AI can analyze data from various sensors on missiles, identifying patterns and anomalies indicative of potential problems. Machine Learning Algorithms: AI algorithms learn from historical maintenance data and sensor readings to predict future component failures. Proactive Maintenance Scheduling: Based on AI predictions, maintenance schedules can be optimized, addressing issues before they impact functionality. Real-time Health Monitoring: AI can continuously monitor missile systems, enabling early detection of problems and faster response times. Benefits of AI-powered Predictive Maintenance for Missiles: Improved System Availability: Predictive maintenance reduces downtime and ensures missiles are ready for deployment when needed. Enhanced Safety and Reliability: Proactive identification of potential failures minimizes the risk of in-flight malfunctions. Reduced Maintenance Costs: Focusing on targeted maintenance based on AI predictions can be more efficient than routine overhauls. Optimized Resource Allocation: Maintenance resources can be prioritized based on AI predictions, ensuring critical issues are addressed first. Challenges and Considerations of AI-powered Predictive Maintenance: Data Quality and Integration: The effectiveness of AI relies on access to high-quality, comprehensive sensor data from missiles and maintenance records. Explainability of AI Predictions: Understanding how AI reaches conclusions about potential failures is crucial for building trust with human maintenance personnel. Integration with Existing Systems: Seamless integration of AI-powered predictive maintenance systems with existing maintenance infrastructure is necessary. The Future of AI and Predictive Maintenance for Missiles: Development of Explainable AI (XAI) for Maintenance Prediction: Making AI's reasoning more transparent to enhance collaboration and trust with human technicians. Advanced Sensor Technologies: Integration of new sensor technologies can provide AI with even richer data for more accurate predictions. Standardization of Data Formats: Developing standardized data formats across different missile systems can facilitate better data integration and analysis. By leveraging AI, we can create a more proactive and efficient approach to missile maintenance. However, ensuring data quality, fostering trust in AI predictions, and integrating with existing systems are crucial for successful implementation. #AI #PredictiveMaintenance #MissileSystems #Maintenance #Reliability #Safety #CostSavings #ResourceAllocation #SensorDataAnalysis #MachineLearning #RealTimeMonitoring #ExplainableAI #DataQuality #Integration #FutureofMaintenance #DefenseTechnology artificial intelligence, predictive maintenance, missile systems, maintenance, reliability, safety, cost savings, resource allocation, sensor data analysis, machine learning, real-time monitoring, explainable AI, data quality, integration, future of maintenance, defense technology #artificialintelligence #ai #machinelearning #deeplearning #dataanalytics #bigdata #futureofwork #futurism #algorithms #automation #aiingujarat #educational #informative #technology #trends #future #disruption #opportunities #challenges #impact #society #humanity #vlog #music #funny #tutorial #challenge #love #gaming #comedy #art #life #cute #travel #fashion #beauty #dance #food #pets #motivation #fitness #trending #gamer #minecraft #fortnite #gta #cod #apexlegends #pubg #valorant #leagueoflegends #roblox #makeup #skincare #hairstyle #beautyhacks #hairstyletutorial #skincaretips #makeuproutine #nails #tech #gadget #review #unboxing #iphone #android #apple #samsung #smartphone #laptop #viral #ai #mobile #movie #shorts #song #game #aiinindia #viral #video #viralvideo #shorts #youtubeshorts #youtube #youtuber #ai #trending #bestvideo #funny #tekthrill www.youtube.com https://youtube.com/@TEKTHRILL?si=rl1JYFFIjD5oqpJ3 Tekthrill The AI Tekthrill Future of AI Keyur Kuvadiya Youtube

Deep Learning Part-2

🚀 Master Deep Learning from Scratch! 🧠💻 Welcome to AI Brillance]! Dive into the fascinating world of Deep Learning with our comprehensive tutorial series. Whether you're a beginner eager to grasp the fundamentals or a seasoned enthusiast looking to enhance your skills, this series has something for everyone. In this tutorial, we'll embark on an exciting journey through the core concepts of Deep Learning. From understanding neural networks to implementing advanced algorithms, we'll cover it all step-by-step. No prior experience? No problem! We'll start with the basics, ensuring that even newcomers can follow along and build a solid foundation. Here's what you can expect from this tutorial: 1. Introduction to Deep Learning: Unravel the mysteries behind neural networks and their applications in real-world scenarios. 2. Hands-on Coding: Get your hands dirty with practical coding exercises using popular libraries like TensorFlow and PyTorch. 3. Advanced Techniques: Explore cutting-edge techniques such as Convolutional Neural Networks (CNNs), Recurrent Neural Networks (RNNs), and Generative Adversarial Networks (GANs). 4. Real-world Projects: Apply your newfound knowledge to exciting projects ranging from image recognition to natural language processing. Join us as we demystify the complexities of Deep Learning and empower you to unleash its full potential. Whether you're a student, researcher, or industry professional, this tutorial series is your gateway to mastering one of the most revolutionary technologies of our time. Don't miss out on the opportunity to elevate your skills and stay ahead in the rapidly evolving field of Artificial Intelligence. Subscribe now and embark on your journey to becoming a Deep Learning expert!

Deep Learning Part-3

Predictive Maintenance: AI Prevents Missile System Failures! Part 8 #ai #viral #trending

Predictive Maintenance: AI Prevents Missile System Failures! Part 8 #ai #viral #trending Keeping missiles mission-ready is critical for national defense. In this video, we'll explore how Artificial Intelligence (AI) is revolutionizing predictive maintenance for missile systems. Why Predictive Maintenance is Crucial for Missiles: High-Tech Systems: Modern missiles are complex systems with numerous components susceptible to wear and tear. Mission-Critical Performance: Missile failures during deployment can have catastrophic consequences. Preventive Maintenance vs. Reactive Repairs: Predicting and addressing potential issues before they escalate is crucial for maintaining readiness. How AI Enables Predictive Maintenance for Missiles: Sensor Data Analysis: AI can analyze data from various sensors on missiles, identifying patterns and anomalies indicative of potential problems. Machine Learning Algorithms: AI algorithms learn from historical maintenance data and sensor readings to predict future component failures. Proactive Maintenance Scheduling: Based on AI predictions, maintenance schedules can be optimized, addressing issues before they impact functionality. Real-time Health Monitoring: AI can continuously monitor missile systems, enabling early detection of problems and faster response times. Benefits of AI-powered Predictive Maintenance for Missiles: Improved System Availability: Predictive maintenance reduces downtime and ensures missiles are ready for deployment when needed. Enhanced Safety and Reliability: Proactive identification of potential failures minimizes the risk of in-flight malfunctions. Reduced Maintenance Costs: Focusing on targeted maintenance based on AI predictions can be more efficient than routine overhauls. Optimized Resource Allocation: Maintenance resources can be prioritized based on AI predictions, ensuring critical issues are addressed first. Challenges and Considerations of AI-powered Predictive Maintenance: Data Quality and Integration: The effectiveness of AI relies on access to high-quality, comprehensive sensor data from missiles and maintenance records. Explainability of AI Predictions: Understanding how AI reaches conclusions about potential failures is crucial for building trust with human maintenance personnel. Integration with Existing Systems: Seamless integration of AI-powered predictive maintenance systems with existing maintenance infrastructure is necessary. The Future of AI and Predictive Maintenance for Missiles: Development of Explainable AI (XAI) for Maintenance Prediction: Making AI's reasoning more transparent to enhance collaboration and trust with human technicians. Advanced Sensor Technologies: Integration of new sensor technologies can provide AI with even richer data for more accurate predictions. Standardization of Data Formats: Developing standardized data formats across different missile systems can facilitate better data integration and analysis. By leveraging AI, we can create a more proactive and efficient approach to missile maintenance. However, ensuring data quality, fostering trust in AI predictions, and integrating with existing systems are crucial for successful implementation. #AI #PredictiveMaintenance #MissileSystems #Maintenance #Reliability #Safety #CostSavings #ResourceAllocation #SensorDataAnalysis #MachineLearning #RealTimeMonitoring #ExplainableAI #DataQuality #Integration #FutureofMaintenance #DefenseTechnology artificial intelligence, predictive maintenance, missile systems, maintenance, reliability, safety, cost savings, resource allocation, sensor data analysis, machine learning, real-time monitoring, explainable AI, data quality, integration, future of maintenance, defense technology #artificialintelligence #ai #machinelearning #deeplearning #dataanalytics #bigdata #futureofwork #futurism #algorithms #automation #aiingujarat #educational #informative #technology #trends #future #disruption #opportunities #challenges #impact #society #humanity #vlog #music #funny #tutorial #challenge #love #gaming #comedy #art #life #cute #travel #fashion #beauty #dance #food #pets #motivation #fitness #trending #gamer #minecraft #fortnite #gta #cod #apexlegends #pubg #valorant #leagueoflegends #roblox #makeup #skincare #hairstyle #beautyhacks #hairstyletutorial #skincaretips #makeuproutine #nails #tech #gadget #review #unboxing #iphone #android #apple #samsung #smartphone #laptop #viral #ai #mobile #movie #shorts #song #game #aiinindia #viral #video #viralvideo #shorts #youtubeshorts #youtube #youtuber #ai #trending #bestvideo #funny #tekthrill www.youtube.com https://youtube.com/@TEKTHRILL?si=rl1JYFFIjD5oqpJ3 Tekthrill The AI Tekthrill Future of AI Keyur Kuvadiya Youtube

Deep learning Part-4

Deep Learning Part - 5

Building Your Own Private GenAI Chatbot With Java Tools – A Step-by-Step Adventure

In today's software development world, several machine learning (ML) tools empower developers to craft private chatbots that cater to various needs. These chatbots harness the capabilities of large language models (LLMs) trained on confidential document sets on your local machine or enterprise data repositories. They enable you to engage with these document sets, from summarizing emails and meeting notes to gauging sentiment, extracting dates and names from websites, pre-screening resumes, and performing many other tasks. But most of these systems are Python-based. While Python is a formidable stream-of-consciousness programming language for ML, many software developers operate within the Java ecosystem, especially within large organizations prioritizing Java for robust and reliable production deployments. This presentation focuses on Java-centric tools to construct tuned assistant systems. Speaker: Frank Greco, Chairman at NYJavaSIG Frank Greco is a Java Champion and enterprise architect primarily focused on artificial intelligence, machine learning, cloud, and mobile/edge computing. He is an educator, technology manager, frequent writer, and author, and he has made visible achievements in strategic technology/business partnerships, enterprise infrastructure, and emerging technologies, particularly for financial systems and large enterprises. He is currently a senior technology consultant for a huge search company. Frank is the co-author of JSR # 318, the Visual Recognition Machine Learning API for Java. He is a frequent global speaker at major technology trade shows such as QCon, DevNexus, Jfokus, Devoxx, Technology Transfer International, JavaOne, etc. Join us: Website: https://jb.gg/website Blog: https://jb.gg/blog Twitter: https://twitter.com/intellijidea Facebook: https://www.facebook.com/IntelliJIDEA/ Download IntelliJ IDEA: https://jb.gg/download-intellij-idea Top 15 IntelliJ IDEA shortcuts: https://jb.gg/Top15IntelliJIDEAShortcuts #ai #chatbot #jetbrains #inetllijidea #intellijideaconf

Fake Parts Exposed: AI Detects Counterfeit Components in Missiles! Part 4 #ai #viral #aiinindia

Fake Parts Exposed: AI Detects Counterfeit Components in Missiles! Part 4 #ai #viral #aiinindia The integrity of a missile system relies on genuine parts. In this video, we'll explore how Artificial Intelligence (AI) is becoming a crucial tool in the fight against counterfeit missile parts. The Threat of Counterfeit Missile Parts: Compromised Reliability and Performance: Counterfeit parts may not meet quality standards, potentially leading to malfunctions or system failures. Safety Risks: Faulty parts can increase the risk of accidents or catastrophic failures during launch or operation. National Security Concerns: Counterfeiting undermines the effectiveness of missile systems, impacting national defense capabilities. How AI Can Detect Counterfeit Missile Parts: Machine Learning for Image Recognition: AI algorithms can analyze high-resolution images of parts, identifying anomalies and discrepancies compared to genuine components. Material Composition Analysis: AI can analyze data from material composition testing equipment (e.g., X-ray fluorescence) to detect deviations from original specifications. Data-driven Pattern Recognition: AI can learn from historical data on known counterfeit parts, identifying patterns and signatures for future detection. Real-time Inspection and Monitoring: AI-powered systems can continuously monitor production lines and stockpiles, flagging suspicious parts for further investigation. Benefits of AI-powered Counterfeit Parts Detection: Enhanced Detection Rates: AI can identify subtle variations in counterfeit parts that might be missed by human inspectors. Increased Efficiency: AI can automate repetitive inspection tasks, freeing up human personnel for more complex analysis. Improved Quality Control: AI can support a more proactive approach to quality control throughout the missile supply chain. Reduced Risk of System Failures: Early detection of counterfeit parts minimizes the risk of malfunctions and accidents. Challenges and Considerations of AI-powered Counterfeit Parts Detection: Access to High-Quality Data: Effective AI training requires a large dataset of images and material composition data from both genuine and counterfeit parts. Evolving Counterfeiting Techniques: AI models need to be continuously updated to keep pace with evolving methods used by counterfeiters. Explainability of AI Decisions: Understanding how AI flags suspicious parts is crucial for building trust and ensuring the accuracy of detections. The Future of AI and Counterfeit Parts Detection: The future offers promising advancements: Development of Explainable AI (XAI) for Part Authentication: Making AI's reasoning more transparent to enhance human oversight and decision-making. Integration with Blockchain Technology: Using blockchain to create tamper-proof records of parts origin and history can further strengthen authentication. Advanced Data Collection and Analysis Tools: Developments in sensor technology and data analysis techniques can provide AI with even richer data for improved detection capabilities. By leveraging AI, we can create a more robust defense against counterfeit missile parts. Addressing data access challenges, adapting to evolving threats, and ensuring transparency in AI decisions are crucial for successful implementation. #AI #CounterfeitParts #MissileDefense #QualityControl #NationalSecurity #MachineLearning #ImageRecognition #MaterialAnalysis #PatternRecognition #RealTimeInspection #ExplainableAI #DataSecurity #EvolvingThreats #Blockchain #FutureofDefense artificial intelligence, counterfeit parts, missile defense, quality control, national security, machine learning, image recognition, material analysis, pattern recognition, real-time inspection, explainable AI #artificialintelligence #ai #machinelearning #deeplearning #dataanalytics #bigdata #futureofwork #futurism #algorithms #automation #aiingujarat #educational #informative #technology #trends #future #disruption #opportunities #challenges #impact #society #humanity #vlog #music #funny #tutorial #challenge #love #gaming #comedy #art #life #cute #travel #fashion #beauty #dance #food #pets #motivation #fitness #trending #gamer #minecraft #fortnite #gta #cod #apexlegends #pubg #valorant #leagueoflegends #roblox #makeup #skincare #hairstyle #beautyhacks #hairstyletutorial #skincaretips #makeuproutine #nails #tech #gadget #review #unboxing #iphone #android #apple #samsung #smartphone #laptop #viral #ai #mobile #movie #shorts #song #game #aiinindia #viral #video #viralvideo #shorts #youtubeshorts #youtube #youtuber #ai #trending #bestvideo #funny #tekthrill www.youtube.com https://youtube.com/@TEKTHRILL?si=rl1JYFFIjD5oqpJ3 Tekthrill The AI Tekthrill Future of AI Keyur Kuvadiya Youtube

Fake Parts Exposed: AI Detects Counterfeit Components in Missiles! Part 5 #ai #viral #aiinindia

Fake Parts Exposed: AI Detects Counterfeit Components in Missiles! Part 5 #ai #viral #aiinindia The integrity of a missile system relies on genuine parts. In this video, we'll explore how Artificial Intelligence (AI) is becoming a crucial tool in the fight against counterfeit missile parts. The Threat of Counterfeit Missile Parts: Compromised Reliability and Performance: Counterfeit parts may not meet quality standards, potentially leading to malfunctions or system failures. Safety Risks: Faulty parts can increase the risk of accidents or catastrophic failures during launch or operation. National Security Concerns: Counterfeiting undermines the effectiveness of missile systems, impacting national defense capabilities. How AI Can Detect Counterfeit Missile Parts: Machine Learning for Image Recognition: AI algorithms can analyze high-resolution images of parts, identifying anomalies and discrepancies compared to genuine components. Material Composition Analysis: AI can analyze data from material composition testing equipment (e.g., X-ray fluorescence) to detect deviations from original specifications. Data-driven Pattern Recognition: AI can learn from historical data on known counterfeit parts, identifying patterns and signatures for future detection. Real-time Inspection and Monitoring: AI-powered systems can continuously monitor production lines and stockpiles, flagging suspicious parts for further investigation. Benefits of AI-powered Counterfeit Parts Detection: Enhanced Detection Rates: AI can identify subtle variations in counterfeit parts that might be missed by human inspectors. Increased Efficiency: AI can automate repetitive inspection tasks, freeing up human personnel for more complex analysis. Improved Quality Control: AI can support a more proactive approach to quality control throughout the missile supply chain. Reduced Risk of System Failures: Early detection of counterfeit parts minimizes the risk of malfunctions and accidents. Challenges and Considerations of AI-powered Counterfeit Parts Detection: Access to High-Quality Data: Effective AI training requires a large dataset of images and material composition data from both genuine and counterfeit parts. Evolving Counterfeiting Techniques: AI models need to be continuously updated to keep pace with evolving methods used by counterfeiters. Explainability of AI Decisions: Understanding how AI flags suspicious parts is crucial for building trust and ensuring the accuracy of detections. The Future of AI and Counterfeit Parts Detection: The future offers promising advancements: Development of Explainable AI (XAI) for Part Authentication: Making AI's reasoning more transparent to enhance human oversight and decision-making. Integration with Blockchain Technology: Using blockchain to create tamper-proof records of parts origin and history can further strengthen authentication. Advanced Data Collection and Analysis Tools: Developments in sensor technology and data analysis techniques can provide AI with even richer data for improved detection capabilities. By leveraging AI, we can create a more robust defense against counterfeit missile parts. Addressing data access challenges, adapting to evolving threats, and ensuring transparency in AI decisions are crucial for successful implementation. #AI #CounterfeitParts #MissileDefense #QualityControl #NationalSecurity #MachineLearning #ImageRecognition #MaterialAnalysis #PatternRecognition #RealTimeInspection #ExplainableAI #DataSecurity #EvolvingThreats #Blockchain #FutureofDefense artificial intelligence, counterfeit parts, missile defense, quality control, national security, machine learning, image recognition, material analysis, pattern recognition, real-time inspection, explainable AI #artificialintelligence #ai #machinelearning #deeplearning #dataanalytics #bigdata #futureofwork #futurism #algorithms #automation #aiingujarat #educational #informative #technology #trends #future #disruption #opportunities #challenges #impact #society #humanity #vlog #music #funny #tutorial #challenge #love #gaming #comedy #art #life #cute #travel #fashion #beauty #dance #food #pets #motivation #fitness #trending #gamer #minecraft #fortnite #gta #cod #apexlegends #pubg #valorant #leagueoflegends #roblox #makeup #skincare #hairstyle #beautyhacks #hairstyletutorial #skincaretips #makeuproutine #nails #tech #gadget #review #unboxing #iphone #android #apple #samsung #smartphone #laptop #viral #ai #mobile #movie #shorts #song #game #aiinindia #viral #video #viralvideo #shorts #youtubeshorts #youtube #youtuber #ai #trending #bestvideo #funny #tekthrill www.youtube.com https://youtube.com/@TEKTHRILL?si=rl1JYFFIjD5oqpJ3 Tekthrill The AI Tekthrill Future of AI Keyur Kuvadiya Youtube

Neo4J as Vector Store with langchain OpenAI and Wikipedia #datascience #machinelearning

In this video I will show you how to use Neo4J as vector Store with Langchain , Wikipedia and Openai embeddings Notebook: https://github.com/olonok69/LLM_Notebooks/blob/main/Neo4j/Neo4J_vector_index_langchain_Openai.ipynb

Intro to Deep Q Learning - Learn Reinforcement Learning with Me

Interested in learning about Deep Q Learning for reinforcement learning? This video is the perfect intro to understanding this important concept in artificial intelligence. I host weekly deep RL study sessions on discord. Join us on thursdays at 10AM Eastern: https://discord.gg/jjVNxjd5 Let's connect: https://bio.blaisep.com

Training the AI Model and Performing Google Searches part4 #techiewithaakash #machinelearning

Training Ai model to automate an task #NumpyPythonTutorial #Numpy #NumpyTutorial #NumpyPython #PythonNumpyTutorial #LearnNumpy #WhatisNumpy #NumpyTutorialforBeginners #PythonNumpyTutorialForBeginners #TechieWithAakash 📌 Do subscribe to the TechieWithAakash channel & get regular updates on videos: https://bit.ly/3SwLJtK Why should you watch this Python tutorial? You can learn Python much faster than any other programming language and this Python tutorial helps you do just that. Python programming is one of the best languages that is finding increased applications for machine learning. you can learn Python Programming and apply it to real-world scenarios like machine learning and data science. (Book your Appointment) [https://calendly.com/nirvriksh/meet-up] (if you want a build any project or product idea you have in mind : Visit Website :) [https://nirvriksh.com/] 🙏🙏🙏🙏🙏🙏🙏🙏 YOU JUST NEED TO DO 3 THINGS to support my channel LIKE SHARE & SUBSCRIBE TO MY YOUTUBE CHANNEL

RAG using Milvus, HuggingFace, LangChain, Ragas, with or without OpenAI

Christy Bergman, Developer Advocate, Zilliz Abstract: You’ve heard good data matters in Machine Learning, but does it matter for Generative AI applications? Corporate data often differs significantly from the general Internet data used to train most foundation models. Join me for a Python demo tutorial on building a customizable RAG (Retrieval Augmented Generation) stack using OSS Milvus vector database, LangChain, Ragas, HuggingFace, and optional Zilliz cloud and OpenAI. Learn best practices and advanced techniques to optimize GenAI workflows with your own data. What you’ll learn: * Using Python, learn how to build a customizable open source RAG (Retrieval Augmented Generation) chatbot with Milvus vector database, LangChain, Ragas, and HuggingFace models, and optional Zilliz cloud and OpenAI. * Best practices around embedding text data ("embedding" in AI is like "featurization" in ML). * Best practices around vector indexing and search. * Best practices around RAG evaluation with Ragas. Tutorial notebook link will be linked here: https://github.com/milvus-io/bootcamp/tree/master/bootcamp Tutorial instructions like this but more focused on running locally: https://docs.google.com/document/d/1yetuGEkYqh_1rAYEBXFAnwsFClMAIQFx1erLHHKXTLg Slides like these: https://docs.google.com/presentation/d/1hpiaiVMHm4oQr5P86NhcrL0qXwBIdWhHEZOlWKySHyM Speaker Bio: 6+ years building AI and ML systems with math and coding. My mission is to help developers and customers use those tools (with fewer heartaches than I had teaching myself) to organize and search unstructured data, such as images, videos, texts, and audios, using LLM and multi-modal apps. I enjoy learning new technologies and tools and solving challenging problems with math and coding. As a Developer Advocate, I use my skills in Python, HuggingFace, PyTorch, Spark, RLlib, Ray distributed computing, and vector databases to create and share engaging and informative content, such as tutorials, demos, blogs, and talks. I also manage the Bay Area Unstructured Data meetup group, where I organize events and foster a community of enthusiasts and experts in the field. Outside of work, I enjoy hiking and bird watching. In my background photo: Australian bustard, spotted near Cairns, Australia. https://www.meetup.com/sf-bay-acm/events/300144563/ Pre-trimmed times: 0:00 Chapter Intro 3:17 Speaker Intro Gap, bad audio & missing first few slides, see link above 10:22 Presentation

Machine Learning Demystified: A Beginner's Guide

Welcome to AI and Beyond - Unraveling the Future of Technology! 🚀 Dive into the fascinating world of data science, artificial intelligence, and Quantum AI with Dr. Joshua Allard, an experienced data scientist and AI researcher. Whether you're a curious beginner, a seasoned professional, or someone in between, this channel is your gateway to understanding some of the most complex and cutting-edge technologies shaping our future. 🧠 What We Offer: In-Depth Tutorials: Step-by-step guides on machine learning algorithms, quantum computing fundamentals, and more. Practical Applications: Real-world applications of AI and data science across various industries, from healthcare to finance, reveal how these technologies transform our world. Advanced Topics: Dive into the intricacies of Quantum AI, exploring how quantum computing is merging with artificial intelligence to unlock new possibilities. Interactive Learning: Engaging content that encourages viewer participation through Q&A sessions, live coding, and interactive polls. 🔍 Why Subscribe? Expert Insights: Leverage Dr. Allard's deep understanding of data science and AI to gain foundational knowledge and advanced expertise. Community of Tech Enthusiasts: Join a growing community of like-minded individuals passionate about technology and its potential to solve complex problems. Stay Updated: Keep up with the latest trends and innovations in AI and quantum technologies as they happen. 👨‍🏫 Who Should Watch? Students and Educators: Enhance your learning or teaching toolkit with accessible educational content. Professionals: Gain competitive knowledge and skills in emerging technologies reshaping industries. Hobbyists and Tech Enthusiasts: Explore fascinating tech topics in a way that is informative but also fun and engaging. 🌟 Join Us on This Journey Subscribe and hit the bell icon to avoid missing any updates as we explore the potential and power of advanced technology. Whether it’s breaking down complex algorithms or showcasing futuristic applications, [Your Channel Name] is here to help you navigate the evolving world of tech. Embrace the future—learn, engage, and grow with us!

Decision Tree Classification Clearly Explained | Machine Learning Tutorial by Ainomo

Unlock the power of decision tree classification with this comprehensive Machine Learning tutorial by Ainomo. Ideal for beginners and advanced practitioners alike, this video will guide you through the concepts and practical implementation of decision trees in machine learning, a fundamental technique used in artificial intelligence for making complex decisions based on simple decision rules. What You'll Learn: What is decision tree classification and how does it work? Step-by-step guide to building a decision tree model in Python. Understanding the mathematics and logic behind decision trees. Best practices for optimizing and tuning decision trees in real-world applications. Explore More: Dive deeper into machine learning and AI on our company page: Ainomo Company Explore the innovative AI technologies we are developing at Ainomo: Ainomo Technology Learn more about our mission and contributions to AI: About Ainomo Stay Connected: Subscribe to our YouTube channel for more detailed tutorials and cutting-edge insights into AI. Follow us on social media to stay updated with the latest trends and developments in artificial intelligence. About Ainomo: At Ainomo, we are passionate about leveraging artificial intelligence to solve real-world problems and improve daily life. Our tutorials aim to demystify AI and machine learning concepts, making them accessible to everyone interested in the field, from students to professionals. Watch Next: Machine Learning Fundamentals: An Introduction How to Improve Your Machine Learning Models with Advanced Algorithms Practical Applications of Machine Learning in Industry Thank you for watching "Decision Tree Classification Clearly Explained | Machine Learning Tutorial by Ainomo." If this video helped clarify decision tree classification for you, please like, share, and comment below with any questions or insights. Don’t forget to subscribe and hit the notification bell to keep up with all our exciting content!

Free AI for Agriculture: Open-Source Tools for BSc Students! Part 2 #ai #viral #trending #aiinindia

Free AI for Agriculture: Open-Source Tools for BSc Students! Part 2 #ai #viral #trending #aiinindia Greetings, budding agricultural scientists, plant enthusiasts, and anyone who wants to be a plant disease detective! Worried about your crops? There's an open-source AI hero waiting to help! Today, we'll explore open-source AI tools for plant disease detection, empowering BSc students to diagnose plant problems with confidence and ease. The Challenge of Plant Disease Identification: Early Detection is Crucial: Identifying plant diseases early is essential for taking timely action and minimizing crop losses. Limited Expertise: Not all farmers have access to professional plant pathologists. The Need for Accessible Diagnostic Tools: BSc students can play a vital role in supporting farmers with accessible tools. How Open-Source AI Tools Help with Plant Disease Detection: Image Recognition with AI: These tools use AI algorithms trained on vast datasets of plant images to identify diseases based on visual symptoms. User-friendly Interfaces: Many open-source tools are designed for ease of use, allowing students to upload plant photos and receive potential diagnoses. Free and Accessible Resources: Open-source nature makes these tools readily available for BSc students to learn and contribute. Benefits of Using Open-Source AI Tools for BSc Students: Develop AI Skills for Agriculture: Students gain practical experience in using AI for a real-world agricultural challenge. Contribute to Open-Source Development: Students can contribute to the improvement of these tools by collecting data and reporting findings. Assist Farmers in Their Communities: Students can use these tools to help local farmers identify plant diseases and improve crop health. Examples of Open-Source AI Tools for Plant Disease Detection: PlantVillage (Focus on a specific tool and its functionalities) OpenCV (Mention other popular tools but don't go into detail) Scikit-image (Mention other popular tools but don't go into detail) Getting Started with Open-Source AI Tools: Online Resources and Tutorials: Numerous online resources and tutorials guide students on using these tools, often with minimal coding experience required. Online Communities: Active online communities provide support and learning opportunities for students using open-source AI tools. The Future of Open-Source AI in Agriculture: Open-source AI tools are democratizing access to AI technology for BSc students in agriculture. In the coming videos in this series, we'll explore other free and accessible open-source AI tools for BSc students, like tools for crop yield prediction or soil analysis using AI. Join us as we delve deeper into the exciting world of open-source AI for agriculture, empowering the next generation of AgTech heroes! #AI #OpenSource #Agriculture #PlantDisease #AIforGood #BSc #Education #Sustainability #FoodSecurity #Technology #FutureofFarming artificial intelligence, open-source, agriculture, plant disease, AI for good, BSc, education, sustainability, food security, technology, future of farming #artificialintelligence #ai #machinelearning #deeplearning #dataanalytics #bigdata #futureofwork #futurism #algorithms #automation #aiingujarat #educational #informative #technology #trends #future #disruption #opportunities #challenges #impact #society #humanity #vlog #music #funny #tutorial #challenge #love #gaming #comedy #art #life #cute #travel #fashion #beauty #dance #food #pets #motivation #fitness #trending #gamer #minecraft #fortnite #gta #cod #apexlegends #pubg #valorant #leagueoflegends #roblox #makeup #skincare #hairstyle #beautyhacks #hairstyletutorial #skincaretips #makeuproutine #nails #tech #gadget #review #unboxing #iphone #android #apple #samsung #smartphone #laptop #viral #ai #mobile #movie #shorts #song #game #aiinindia #viral #video #viralvideo #shorts #youtubeshorts #youtube #youtuber #ai #trending #bestvideo #funny #tekthrill www.youtube.com https://youtube.com/@TEKTHRILL?si=rl1JYFFIjD5oqpJ3 Tekthrill The AI Tekthrill Future of AI Keyur Kuvadiya Youtube

Learn AI automation | Artificial intelligence |Learn AI Course | How to learn AI for beginners

Hi You are welcome to Tech World Rahee @techworldrahee Channel, Learn AI automation | Artificial intelligence |Learn AI Course | How to learn AI for beginners #trick, #technology, #tech, Tech World Rahee Ambika Rahee ****************************************************************************** The channel may explore various technical subjects, such as programming, software development, web design, cybersecurity, data analysis, and more. The goal of a technical YouTube channel is to educate and inform viewers about technical subjects in an engaging and accessible way. Search Tags: technology, टेक्नोलॉजी, Computer, in, of, for, India, Free, Machine, Online, Find, How, New, How To, Latest Update, update, World, Best, Data, Bharat, Windows, Tech World Rahee, Ambika Rahee Channel, Ambika Bhai, Ambika tech channel, Review, How-to, Tutorials, Latest, Technology, Programming,Software development,Web design,Cybersecurity,Data analysis,Artificial,intelligence,Machine learning,Networking,Cloud computing,Coding,Hacking,Tech news,Reviews,Tutorial,How-to,Tips,Tricks,Best practices,Tools,Analysis,Insights, Technology, tech support, tech, hindi tech, hindi tech youtuber, Ambika rahee channel, ambika bhai channel,अम्बिका राही चैनल, अम्बिका भाई चैनल,#computer Tips, #techgyan,#Ambika Rahee, shorts, review, Technology, Tech, Gadgets, Electronics, Reviews, Unboxing, Computers, Laptops, Smartphones, Gaming, Software,Hardware, How-to, Tutorials, Programming, AI (Artificial Intelligence), Machine Learning, Internet of Things (IoT), Cybersecurity, Virtual Reality (VR), Augmented Reality (AR), Wearable Technology, Future Tech, Tech News, Apple, Android, Microsoft, Google, Social Media, Digital Marketing इस चैनल पर आपको टेक्नोलॉजी से जुडी, नई नई विडियो मिलेंगी, जो आप के हमेशा काम आयेंगी, इसलिए चैनल को सब्सक्राइब करके घंटी दबा दीजिये | धन्यवाद! **************************************************************************************** Subscribe the channel for the new update. And like and share if you think best technology channel on you tube: Facebook Page: https://www.facebook.com/technicalworldrahee/?modal=admin_todo_tour Tech world rahee blogs: https://techworldrahee.blogspot.com/ For Biography or Gazal Shayari click Below link https://www.poemgazalshayari.in/ For Tech Article: https://www.poemgazalshayari.in/search/label/Technology Social Handle: Facebook: www.facebook.com/ambikarahee.prasad Twitter: www.twitter.com/Araheeji Instagram: www.instagram.com/ambika_rahee Youtube: www.youtube.com/techworldrahee Background Music: Youtube Audio Library Disclaimer: Educational Purpose The creators of Tech World Rahee make every effort to ensure the accuracy and reliability of the information provided. However, the content should not be considered as exhaustive, up-to-date, or error-free. Views and opinions expressed on this channel are solely those of the creators and do not necessarily represent the views of any educational institution, organization, or individual mentioned. Copyright Disclaimer: Copyright Disclaimer Under Section 107 of the C. Disclaimer - video is for educational purpose only. Copyright Disclaimer Under Section 107 of the Copyright Act 1976, allowance is made for "fair use" for purposes such as criticism, comment, news reporting, teaching, scholarship, and research.

Top 25 AI QA for Jobs Interview | Machine Learning Support Vector Machine | AI Asaan Hai

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Easy Maths for Machine Learning and Deep Learning | AI Asaan HAI

Thursday, April 25, 2024

Mitigating Environmental Risks: AI Assesses Impact of Missile Launches! Part 4 #ai #viral #trending

Mitigating Environmental Risks: AI Assesses Impact of Missile Launches! Part 4 #ai #viral #trending Missile launches are crucial for defense and space exploration, but they can also have a negative environmental impact. In this video, we'll explore how Artificial Intelligence (AI) can be used to minimize the environmental impact of missile launches through enhanced environmental impact assessments (EIAs). Environmental Concerns of Missile Launches: Rocket Exhaust Emissions: Rocket exhaust releases pollutants impacting air quality and contributing to climate change. Noise Pollution: Sonic booms and launch noises can disrupt ecosystems and harm wildlife. Debris and Fallout: Falling debris can cause damage and release hazardous materials into the environment. How AI Can Revolutionize EIAs for Missile Launches: Advanced Modeling and Simulation: AI can model and predict the dispersion of rocket exhaust plumes, noise propagation, and debris trajectory. Data-driven Impact Assessment: AI can analyze historical data and weather patterns to create more accurate assessments of environmental impacts. Optimization of Launch Parameters: AI can suggest adjustments to launch trajectories and fuel types to minimize environmental footprint. Benefits of AI-powered Environmental Impact Assessments: Reduced Environmental Impact: AI can help develop launch strategies that minimize air pollution, noise disturbance, and debris dispersal. Improved Decision-Making: More accurate EIAs powered by AI can inform better decisions about launch timing and environmental mitigation strategies. Sustainable Development of Space Exploration: AI can pave the way for cleaner and more sustainable launches for future space programs. Challenges and Considerations of AI-powered EIAs: Data Availability and Quality: The effectiveness of AI relies on access to comprehensive and accurate environmental data for model training. Transparency and Explainability: Understanding how AI models reach conclusions about environmental impact is crucial for building trust. Integration with Launch Systems: Ensuring seamless integration of AI-powered EIAs with existing launch control systems is necessary. The Future of AI and Environmental Impact Assessment for Launches: The future offers promising advancements: Development of Explainable AI (XAI) for Environmental Modeling: Making AI's reasoning more transparent to build trust and improve collaboration. Real-time Monitoring and Adjustment: AI can analyze real-time environmental data during launch to adjust strategies for minimal impact. International Collaboration on AI for Sustainable Space Exploration: Shared knowledge and resources can accelerate the development of AI for cleaner launches globally. By leveraging AI, we can develop more comprehensive EIAs and optimize launch strategies to minimize the environmental impact of missile launches. However, addressing data needs, ensuring transparency in AI models, and integrating with existing systems are key for successful implementation. #AI #EnvironmentalImpact #MissileLaunch #EIA #RocketExhaust #NoisePollution #Debris #Modeling #Simulation #DataAnalysis #Optimization #SustainableSpace #XAI #RealTimeMonitoring #InternationalCollaboration artificial intelligence, environmental impact, missile launch, environmental impact assessment, rocket exhaust, noise pollution, debris, modeling, simulation, data analysis, optimization, sustainable space exploration, explainable AI, real-time monitoring, international collaboration, space exploration #artificialintelligence #ai #machinelearning #deeplearning #dataanalytics #bigdata #futureofwork #futurism #algorithms #automation #aiingujarat #educational #informative #technology #trends #future #disruption #opportunities #challenges #impact #society #humanity #vlog #music #funny #tutorial #challenge #love #gaming #comedy #art #life #cute #travel #fashion #beauty #dance #food #pets #motivation #fitness #trending #gamer #minecraft #fortnite #gta #cod #apexlegends #pubg #valorant #leagueoflegends #roblox #makeup #skincare #hairstyle #beautyhacks #hairstyletutorial #skincaretips #makeuproutine #nails #tech #gadget #review #unboxing #iphone #android #apple #samsung #smartphone #laptop #viral #ai #mobile #movie #shorts #song #game #aiinindia #viral #video #viralvideo #shorts #youtubeshorts #youtube #youtuber #ai #trending #bestvideo #funny #tekthrill www.youtube.com https://youtube.com/@TEKTHRILL?si=rl1JYFFIjD5oqpJ3 Tekthrill The AI Tekthrill Future of AI Keyur Kuvadiya Youtube

Deep Learning and AI Spring 2024 L06: Basic building block of LLMs

------------------------------------------------------------------------------------------------- Below are playlists on ML, Data Science, AI, MLOps/AIOps and Deep Learning. Please subscribe and support the channel. Happy Learning! 1. MLOps Playlist: https://www.youtube.com/playlist?list=PLzq3B7Hh4uvZ1FNqVsl-E5FTtoOwhEofi 2. Deep Learning Playlist: https://youtube.com/playlist?list=PLzq3B7Hh4uvaPVjvXQeuD98eGNfqLyJ2G 3. Machine Learning Playlist: https://youtube.com/playlist?list=PLzq3B7Hh4uva3b8LXS_MryJNKyj-xz2qT 4. Probability Refresher for Business Analytics and Machine Learning: https://youtube.com/playlist?list=PLzq3B7Hh4uva2qkiTJHjWMkdg_Ng2KYgb 5. Linear Algebra Primer for Business Analytics and Machine Learning: https://youtube.com/playlist?list=PLzq3B7Hh4uvZpOMDIpBWtOHsgnK0LLkJ- ------------------------------------------------------------------------------------------------- ------------------------------------------------------------------------------------------------- Connect with me here: Twitter: https://twitter.com/ttulabandhula Email: hey@theja.org Web: https://www.theja.org

Unlock the Power: AI Class 2 Tips and Tricks Exposed!

In this groundbreaking video, we delve into the realm of Artificial Intelligence Class 2, uncovering its mysteries and revealing expert insights. Get ready to embark on a journey of discovery as we explore the intricacies of AI Class 2 and how it's shaping the future. #ai #artificialintelligence #Class1 #machinelearning #datascience #innovation #technology #learning #futuretech

Naive Bayes Classifier Python Tutorial | Machine Learning Basics with Ainomo

Dive into the essentials of machine learning with Ainomo's detailed tutorial on the Naive Bayes Classifier in Python. This video provides a comprehensive guide on how to implement this powerful probabilistic classifier, which is widely used in the field of artificial intelligence for making predictions and decisions based on data. What You'll Learn: An introduction to the Naive Bayes Classifier and its applications in machine learning. Step-by-step guide on implementing the Naive Bayes Classifier in Python. Tips and best practices for enhancing the accuracy and efficiency of your machine learning models. How Naive Bayes fits into the broader landscape of AI technologies. Explore More: Learn more about how Ainomo is pioneering in AI and machine learning technologies on our company page: Ainomo Company Discover the cutting-edge AI technologies we’re developing: Ainomo Technology Find out more about our vision and projects in AI: About Ainomo Stay Connected: Subscribe to our YouTube channel for more tutorials, insights, and updates on the latest in AI and machine learning. Follow us on social media to stay ahead of the curve in the rapidly evolving field of artificial intelligence. About Ainomo: Ainomo is dedicated to advancing artificial intelligence through innovative research and practical applications. Our tutorials are designed to empower developers, data scientists, and enthusiasts to harness the full potential of AI tools in their projects and careers. Watch Next: Introduction to Machine Learning with Python Advanced Techniques in Machine Learning: Beyond the Basics Real-World Applications of Naive Bayes in AI Thank you for watching "Naive Bayes Classifier Python Tutorial | Machine Learning Basics with Ainomo". If you enjoyed this video and found it helpful, please give it a thumbs up, share it, and comment below with any questions or feedback. Subscribe and click the bell icon to receive notifications for our latest videos and never miss an update from us!

MRI Brain Tumor Segmentation Using ResUNet Deep Learning Architecture

Call or WhatsApp +91-8909603708 for Research Projects Deep Learning for Brain Tumor Segmentation: Utilizing ResUNet Architecture In this video, we delve into the realm of medical imaging and showcase how advanced AI techniques, specifically utilizing the ResUNet deep learning architecture, can be employed for the crucial task of brain tumor segmentation. Leveraging publicly available data from Kaggle, we explore the implementation of a custom deep learning model to accurately detect and localize brain tumors in MRI scans. We provide insights into the key components of the ResUNet architecture, emphasizing its effectiveness in handling medical image data. Additionally, we discuss the importance of feature extraction, convolutions, and convolutional neural network (CNN) visualization techniques in understanding the inner workings of the model. One of the critical aspects of our approach is the utilization of a custom loss function tailored for brain tumor segmentation tasks. We draw upon resources from the open-source community, specifically the Focal Tversky loss function, to enhance the training process and improve the model's performance. Throughout the video, we highlight the significance of transfer learning in medical imaging applications, citing valuable resources by experts such as Dipanjan Sarkar and Jason Brownlee. By leveraging pre-trained models and fine-tuning them for specific tasks, we can achieve superior results with reduced computational overhead. By the end of this video, viewers will gain a comprehensive understanding of how AI-powered techniques can revolutionize healthcare, particularly in the early detection and precise localization of brain tumors. Join us on this journey as we explore the intersection of deep learning and medical imaging, paving the way for advancements in diagnosis and treatment. Code File: https://github.com/sachin365123/MRI-Brain-Tumor-Segmentation-Using-ResUNet-Deep-Learning-Architecture-/tree/main - Data source: https://www.kaggle.com/mateuszbuda/lgg-mri-segmentation - Clickable link for the full list of startups in AI medical imagery: https://research.aimultiple.com/looking-for-better-medical-imaging-for-early-diagnostic-and-monitoring-contact-the-leading-vendors-here/ - Feature Extraction and Convolutions: https://setosa.io/ev/image-kernels/ - CNN Visualization: https://www.cs.ryerson.ca/~aharley/vis/conv/flat.html #AI #MedicalImaging #DeepLearning #CNN #TransferLearning #FeatureExtraction #Convolution #LossFunction #ResUNet #startupsindia - Excellent Resource on transfer learning by Dipanjan Sarkar: https://towardsdatascience.com/a-comprehensive-hands-on-guide-to-transfer-learning-with-real-world-applications-in-deep-learning-212bf3b2f27a - Article by Jason Brownlee: https://machinelearningmastery.com/transfer-learning-for-deep-learning/ #datascience #kaggle Loss function: #machinelearning #atal #python #aiinhealthcare #applicationintegration We need a custom loss function to train this ResUNet.So, we have used the loss function as it is from https://github.com/nabsabraham/focal-tversky-unet/blob/master/losses.py #DeepLearning #MedicalImaging #BrainTumorSegmentation #ResUNet #AIinHealthcare #TransferLearning #FocalTverskyLoss #Kaggle #Neuroscience #MachineLearning #BrainTumor #Segmentation #NeuralNetworks #MedicalResearch #DataScience NOW YOU KNOW HOW TO APPLY AI TO DETECT AND LOCALIZE BRAIN TUMORS. THIS IS A GREAT ACHIEVEMENT IN HEALTHCARE. Decoding Brain Tumors: A Deep Learning Journey with ResUNet Unleashing AI in Healthcare: Brain Tumor Detection using ResUNet Empowering Medicine: ResUNet for Accurate Brain Tumor Segmentation Breaking Barriers: ResUNet's Role in Precision Brain Tumor Diagnosis AI Innovations in Medical Imaging: ResUNet for Brain Tumor Localization ResUNet Revolution: Transforming Brain Tumor Detection with Deep Learning Beyond Diagnosis: ResUNet's Impact on Brain Tumor Treatment Planning The Future of Neuroimaging: ResUNet's Promise for Brain Tumor Analysis Unlocking Insights: Exploring Brain Tumor Segmentation with ResUNet Empowering Clinicians: Deep Learning Insights with ResUNet for Brain Tumor Detection Mastering Brain Tumor Detection: The ResUNet Approach Advancing Healthcare: ResUNet's Breakthrough in Brain Tumor Analysis Precision Medicine: ResUNet's Contribution to Brain Tumor Segmentation ResUNet: Redefining Brain Tumor Diagnosis with Deep Learning Leading the Way: ResUNet's Impact on Brain Tumor Localization ResUNet: Pioneering the Future of Neuroimaging in Brain Tumor Detection Insights into Brain Tumor Segmentation: Unveiling ResUNet's Potential ResUNet in Action: Revolutionizing Brain Tumor Detection and Localization Shaping the Future of Medicine: ResUNet's Role in Brain Tumor Analysis ResUNet Unveiled: Exploring the Depths of Brain Tumor Segmentation

Fully Connected Layer Explanation

Discover the power of fully connected layers in regular neural networks! Dive into how these layers process inputs from the preceding layer, compute class scores, and generate outputs in a 1D array, each representing a class. Explore more about fully connected layers and regular neural networks with us!" Fully Connected Layer, Regular Neural Network, Neural Network Basics, Deep Learning, Artificial Intelligence, Machine Learning, Neural Network Architecture, Deep Learning Concepts, Deep Learning Explained, Neural Network Tutorial, Fully Connected Layer Explained, Regular Neural Network Explained, Deep Learning Algorithms, Neural Network Training, Neural Network Models, Deep Learning for Beginners, AI Concepts.