Free artificial intelligence and machine learning video tutorial resource: October 2021

Sunday, October 31, 2021

Github Copilot 🔥🔥 #AI #Machinelearning #NLP

Don't need to sweat out for writing simple code snippets anymore, sign up for Github Copilot preview mode and try it out today. https://copilot.github.com/

COLLEGE KAB OPEN HONGE ? YOUR DOUBTS _| SYLLABUS OF 1st YEAR | #ENGINEERING

Hey everyone This is Ujjwal kapil B.tech 2nd year Ai and Ml In this video we covered one of the most important question "COLLEGE KAB OPEN HONGE " Join us on telegram Group https://t.me/Ujjwalkapil09 All weekly episode are available on Spotify https://open.spotify.com/episode/7FlM... Jiosaavn https://www.jiosaavn.com/shows/the-sp... google podcast https://www.google.com/podcasts?feed=... anchor.fm https://anchor.fm/ujjwal-kapil/episod... Website by me- https://ujjwalkapil09.github.io/roses... Connect with me on LinkedIn- https://www.linkedin.com/in/ujjwal-ka... follow me on Instagram https://www.instagram.com/ujjwal091102/ Facebook -https://www.facebook.com/ujjwal.kapil.90 Mic I use -----https://amzn.to/3jcV0Yb Laptop --- https://amzn.to/3vzmpZD phone used while recording-- https://amzn.to/2XmBeln #python #pythonprogramming #pythontutorial #pythontutorialforbeginners #pythontutorialforbeginnersinhindi #ujjwalkapil #artificial intelligence,#machine learning,what is artificial intelligence,artificial intelligence tutorial,artificial intelligence and machine learning,machine learning vs artificial intelligence,artificial intelligence tutorial for beginners,machine learning tutorial,simplilearn artificial intelligence,artificial intelligence explained,artificial intelligence course,artificial intelligence edureka,artificial intelligence vs machine learning vs deep learning PANTNAGAR govind ballabh pant institute of engineering and technology pauri pauri garwal govind ballabh pant university of agriculture and technology

[YTalks] Siraj Raval - Stories about YouTube, Plagiarism, and the Dangers of Fame (Interview)

#ytalks #siraj #plagiarism A conversation with Siraj Raval about his journey on YouTube, and the perils of fame. OUTLINE: 0:00 - Intro 1:30 - Welcome 3:15 - Starting out: From Economics to YouTube 13:00 - More Views: Plagiarizing Video Content 23:30 - One Step Up: Copying A Research Paper 29:15 - Was there another way? 39:00 - Clickbait Course: Make Money with Machine Learning 50:30 - Rock Bottom and the Way Forward 1:01:30 - Advice for Future Generations Siraj's Channel: https://www.youtube.com/c/SirajRaval Links: TabNine Code Completion (Referral): http://bit.ly/tabnine-yannick YouTube: https://www.youtube.com/c/yannickilcher Twitter: https://twitter.com/ykilcher Discord: https://ift.tt/3dJpBrR BitChute: https://ift.tt/38iX6OV Minds: https://ift.tt/37igBpB Parler: https://ift.tt/38tQU7C LinkedIn: https://ift.tt/3qcgOFy BiliBili: https://ift.tt/3mfyjkW 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/2DuKOZ3 Patreon: https://ift.tt/390ewRH Bitcoin (BTC): bc1q49lsw3q325tr58ygf8sudx2dqfguclvngvy2cq Ethereum (ETH): 0x7ad3513E3B8f66799f507Aa7874b1B0eBC7F85e2 Litecoin (LTC): LQW2TRyKYetVC8WjFkhpPhtpbDM4Vw7r9m Monero (XMR): 4ACL8AGrEo5hAir8A9CeVrW8pEauWvnp1WnSDZxW7tziCDLhZAGsgzhRQABDnFy8yuM9fWJDviJPHKRjV4FWt19CJZN9D4n

Saturday, October 30, 2021

Finally, Beautiful Elastic Simulations Are Here! 🦖🌵

❤️ Check out the Gradient Dissent podcast by Weights & Biases: http://wandb.me/gd 📝 The paper "Medial IPC: accelerated incremental potential contact with medial elastics" is available here: https://ift.tt/3Cu6Ftv https://ift.tt/3Es9fRe 🙏 We would like to thank our generous Patreon supporters who make Two Minute Papers possible: Aleksandr Mashrabov, Alex Haro, Andrew Melnychuk, Angelos Evripiotis, Benji Rabhan, Bryan Learn, Christian Ahlin, Eric Haddad, Eric Martel, Gordon Child, Ivo Galic, Jace O'Brien, Javier Bustamante, John Le, Jonas, Kenneth Davis, Klaus Busse, Lorin Atzberger, Lukas Biewald, Matthew Allen Fisher, Mark Oates, Michael Albrecht, Michael Tedder, Nikhil Velpanur, Owen Campbell-Moore, Owen Skarpness, Rajarshi Nigam, Ramsey Elbasheer, Steef, Taras Bobrovytsky, 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/2icTBUb Thumbnail background design: Felícia Zsolnai-Fehér - http://felicia.hu Meet and discuss your ideas with other Fellow Scholars on the Two Minute Papers Discord: https://ift.tt/2TnVBd3 Károly Zsolnai-Fehér's links: Instagram: https://ift.tt/2KBCNkT Twitter: https://twitter.com/twominutepapers Web: https://ift.tt/1NwkG9m

Friday, October 29, 2021

[ML News] NVIDIA GTC'21 | DeepMind buys MuJoCo | Google predicts spreadsheet formulas

#gtc21 #mlnews #mujoco Register to GTC'21 and Win a RTX 3090: https://nvda.ws/2Y2B5ni OUTLINE: 0:00 - Intro 0:15 - Sponsor: NVIDIA GTC'21 5:35 - DeepMind buys & Open-Sources MuJoCo 7:25 - PyTorch 1.10 Released 9:10 - Google Predicts Spreadsheet Formulas 11:25 - handtracking.io 12:25 - Cell Instance Segmentation Challenge 13:00 - Helpful Libraries 17:50 - Waymo cars keep turning into same dead-end 19:35 - BlueRiver balances tractors References: DeepMind buys & open-sources MuJoCo https://ift.tt/3lPKdot PyTorch 1.10 released https://ift.tt/3lXL3Qd https://ift.tt/2ZAZKjC GoogleAI predicts spreadsheet formulas https://ift.tt/3prpWIp Handtracking in Browser https://ift.tt/3mDWMmc https://ift.tt/3FYS6jw Sartorius Cell Instance Segmentation Competition https://ift.tt/3vV80XA Helpful Libraries https://ift.tt/3jl91Dt https://ift.tt/3aRG3Gy https://ift.tt/3Eu146V https://ift.tt/34duiYE https://ift.tt/3mma8Vb https://ift.tt/3vVLY7b https://ift.tt/3jOrSa8 https://ift.tt/3jkEW42 https://ift.tt/3kldjsY Waymo cars keep coming to same dead-end over and over https://ift.tt/3p6UKOe BlueRiver balances tractors https://ift.tt/31fvGuH https://ift.tt/3pP3h8R Links: TabNine Code Completion (Referral): http://bit.ly/tabnine-yannick YouTube: https://www.youtube.com/c/yannickilcher Twitter: https://twitter.com/ykilcher Discord: https://ift.tt/3dJpBrR BitChute: https://ift.tt/38iX6OV Minds: https://ift.tt/37igBpB Parler: https://ift.tt/38tQU7C LinkedIn: https://ift.tt/3qcgOFy BiliBili: https://ift.tt/3mfyjkW 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/2DuKOZ3 Patreon: https://ift.tt/390ewRH Bitcoin (BTC): bc1q49lsw3q325tr58ygf8sudx2dqfguclvngvy2cq Ethereum (ETH): 0x7ad3513E3B8f66799f507Aa7874b1B0eBC7F85e2 Litecoin (LTC): LQW2TRyKYetVC8WjFkhpPhtpbDM4Vw7r9m Monero (XMR): 4ACL8AGrEo5hAir8A9CeVrW8pEauWvnp1WnSDZxW7tziCDLhZAGsgzhRQABDnFy8yuM9fWJDviJPHKRjV4FWt19CJZN9D4n

[ML News GERMAN] NVIDIA GTC'21 | DeepMind kauft MuJoCo | Google Lernt Spreadsheet Formeln

#gtc21 #mlnews #mujoco Registere für GTC'21 und gewinne eine RTX 3090: https://nvda.ws/2Y2B5ni OUTLINE: 0:00 - Intro 0:15 - Sponsor: NVIDIA GTC'21 6:10 - DeepMind kauft & Open-Sourct MuJoCo 9:05 - PyTorch 1.10 Veröffentlicht 11:25 - Google Lernt Spreadsheet Formeln 14:15 - handtracking.io 15:25 - Zellinstanzsegmentierungswettbewerb 16:15 - Hilfreiche Bibliotheken 23:15 - Waymo autos verirren sich alle in der selben Sackgasse 24:50 - BlueRiver balanciert Traktoren References: DeepMind kauft & open-sourct MuJoCo https://ift.tt/3lPKdot PyTorch 1.10 veröffentlicht https://ift.tt/3lXL3Qd https://ift.tt/2ZAZKjC GoogleAI sagt Tabellen-Formeln voraus https://ift.tt/3prpWIp Handtracking im Browser https://ift.tt/3mDWMmc https://ift.tt/3FYS6jw Sartorius Zellinstanzsegmentierungswettbewerb https://ift.tt/3vV80XA Hilfreiche Bibliotheken https://ift.tt/3jl91Dt https://ift.tt/3aRG3Gy https://ift.tt/3Eu146V https://ift.tt/34duiYE https://ift.tt/3mma8Vb https://ift.tt/3vVLY7b https://ift.tt/3jOrSa8 https://ift.tt/3jkEW42 https://ift.tt/3kldjsY Waymo Autos verirren sich in dieselbe Sackgasse wieder und wieder https://ift.tt/3p6UKOe BlueRiver balanciert Traktoren https://ift.tt/31fvGuH https://ift.tt/3pP3h8R Links: TabNine Code Completion (Referral): http://bit.ly/tabnine-yannick YouTube: https://www.youtube.com/c/yannickilcher Twitter: https://twitter.com/ykilcher Discord: https://ift.tt/3dJpBrR BitChute: https://ift.tt/38iX6OV Minds: https://ift.tt/37igBpB Parler: https://ift.tt/38tQU7C LinkedIn: https://ift.tt/3qcgOFy BiliBili: https://ift.tt/3mfyjkW 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/2DuKOZ3 Patreon: https://ift.tt/390ewRH Bitcoin (BTC): bc1q49lsw3q325tr58ygf8sudx2dqfguclvngvy2cq Ethereum (ETH): 0x7ad3513E3B8f66799f507Aa7874b1B0eBC7F85e2 Litecoin (LTC): LQW2TRyKYetVC8WjFkhpPhtpbDM4Vw7r9m Monero (XMR): 4ACL8AGrEo5hAir8A9CeVrW8pEauWvnp1WnSDZxW7tziCDLhZAGsgzhRQABDnFy8yuM9fWJDviJPHKRjV4FWt19CJZN9D4n

Wednesday, October 27, 2021

Autonomous No-Code AI for Complex Machine Learning Problems

No-Code /Low-Code AI to solve complex problems that requires advanced machine learning. Such problems may range from event recognition, drug discovery, protein or DNA sequencing. For more information visit https://evercot.ai

STRINGS | VARIOUS FUNCTION IN STRING | VIDEO 5| PYTHON CRASH COURSE VIDEO 04 | PYTHON PROGRAMMING

Hey everyone This is Ujjwal kapil B.tech 2nd year Ai and Ml this we are starting are series in which we are covering every basic concept of Python programming Language I assure you that if you continue ths series with me you will be able to solve basic question of python and we are also going to do live question practice of python so what you have to do is just subscribe the channel so that you can get every video and update on time Join us on telegram Group https://t.me/Ujjwalkapil09 ----------------------------------------------------------------------------------------------------- UTU site--https://uktech.ac.in/ All weekly episode are available on Spotify https://open.spotify.com/episode/7FlM... Jiosaavn https://www.jiosaavn.com/shows/the-sp... google podcast https://www.google.com/podcasts?feed=... anchor.fm https://anchor.fm/ujjwal-kapil/episod... Website by me- https://ujjwalkapil09.github.io/roses... Connect with me on LinkedIn- https://www.linkedin.com/in/ujjwal-ka... follow me on Instagram https://www.instagram.com/ujjwal091102/ Facebook -https://www.facebook.com/ujjwal.kapil.90 Mic I use -----https://amzn.to/3jcV0Yb Laptop --- https://amzn.to/3vzmpZD phone used while recording-- https://amzn.to/2XmBeln #python #pythonprogramming #pythontutorial #pythontutorialforbeginners #pythontutorialforbeginnersinhindi #ujjwalkapil #artificial intelligence,#machine learning,what is artificial intelligence,artificial intelligence tutorial,artificial intelligence and machine learning,machine learning vs artificial intelligence,artificial intelligence tutorial for beginners,machine learning tutorial,simplilearn artificial intelligence,artificial intelligence explained,artificial intelligence course,artificial intelligence edureka,artificial intelligence vs machine learning vs deep learning PANTNAGAR govind ballabh pant institute of engineering and technology pauri pauri garwal govind ballabh pant university of agriculture and technology

Deep learning Material | Deep Learning in Telugu | Deep Learning Tutorials in Telugu | #pythonlife

GitHub link: https://github.com/kiransagar1 instagram-link: https://www.instagram.com/pythonlifetelugu/?hl=en Facebook link: https://m.facebook.com/Python-life-telugu-107111387790463/ linkedin: https://www.linkedin.com/in/kiran-sagar-a00a761b2 telegramlink: https://t.me/python_life_telugu Follow this links: 🐍Python full course🐍 https://youtube.com/playlist?list=PLbMVPNscUopThUm8Hdh9vGt4fuYFEXLMw 🗣️Django full course🗣️ https://youtube.com/playlist?list=PLbMVPNscUopRV2oGsRpNeYECVyZ-6KP9v 🐎Machine learning full course🐎 https://youtube.com/playlist?list=PLbMVPNscUopRi0Xm0sIMrFgcUt9ghbnm_ 🖥️Opencv Full course🖥️ https://youtube.com/playlist?list=PLbMVPNscUopSMQQ0JjULjYejx_GX2BrFD 🕺🏻Python Projects🕺🏻 https://youtube.com/playlist?list=PLbMVPNscUopStOJX4rxuJCu2R2mtzmUn0 🙏Opencv Projects🙏 https://youtube.com/playlist?list=PLbMVPNscUopReIPOWXoCz-0tUkykcVOWg 🐅Machine learning projects🐅 https://youtube.com/playlist?list=PLbMVPNscUopSXXPS2zZ7HopmQRWTaUBPI Data Science https://youtube.com/playlist?list=PLbMVPNscUopT-F2Cb9gPzth38S6SambFU Deep Learning https://youtube.com/playlist?list=PLbMVPNscUopSlRw3TSj3Dq9cbzW7AK97q Mock Interviews: https://youtube.com/playlist?list=PLbMVPNscUopTL7dhNMB6AjtDTB8Ehbeqk Career suggestions with Data Scientist: https://youtube.com/playlist?list=PLbMVPNscUopQmuIN-xbL9u0t646Itl7lG Flask: https://youtube.com/playlist?list=PLbMVPNscUopQM1LHytgb2ePWH9QSZfnBv Mongodb: https://youtube.com/playlist?list=PLbMVPNscUopQbvW-xJqm_m6td3sHxzPvn 😌beginner guidance and all your doubts clarifications😌 https://youtube.com/playlist?list=PLbMVPNscUopR4wTAcVoTQgZXLOa4T7_8W deep learning tutorial, deep learning projects, deep learning krish naik, deep learning andrew ng, deep learning ai, deep learning in hindi, deep learning full course, deep learning course, deep learning algorithms, deep learning aktu, deep learning ace academy, deep learning applications, deep learning and machine learning, deep learning and neural networks, deep learning biology, deep learning by krish naik, deep learning basics, deep learning by andrew ng, deep learning beginner, deep learning book, deep learning by mitesh khapra, deep learning by phd scholar, deep learning code with harry, deep learning coursera, deep learning cnn, deep learning cs7015, deep learning crash course, deep learning channel, deep learning computer vision, c language deep learning, deep learning c'est quoi, deep learning definition, deep learning deeplizard, deep learning devcon 2021, deep learning documentary, deep learning deepmind, deep learning data science, deep learning demo, deep learning deployment, deep learning edureka, deep learning engineer, deep learning end to end project, deep learning explained, deep learning example, deep learning explained in hindi, deep learning engineer salary, deep learning examples in real life, deep learning for computer vision nptel, deep learning full course in hindi, deep learning freecodecamp, deep learning from scratch, deep learning for computer vision, deep learning fundamentals, deep learning for data science, deep learning great learning, deep learning game, deep learning gpu, deep learning google, deep learning genomics, deep learning gan, deep learning geoffrey hinton, deep learning gru, deep learning hindi, deep learning harry, deep learning hardware, deep learning harvard, deep learning history, deep learning hype, deep learning hardware requirements, deep learning hands on course, deep learning interview questions, deep learning in tamil, deep learning in telugu, deep learning in python, deep learning iit madras, deep learning introduction, deep learning in malayalam, is deep learning overhyped, deep learning jobs, deep learning java, deep learning jupyter notebook, deep learning jetson nano, deep learning jeremy howard, deep learning javascript, deep learning js, deep learning jobs for freshers, deep learning kya hai, deep learning kya hota hai, deep learning keras, deep learning khapra, deep learning kelly howell, deep learning keras tutorial, deep learning lectures, deep learning laptop, deep learning live, deep learning lex fridman, deep learning live projects, deep learning layers, deep learning laptop requirements, deep learning lizard, deep learning mit, deep learning mcq, deep learning mitesh khapra, deep learning malayalam, deep learning matlab, deep learning models, deep learning music, deep learning meaning, deep learning iitm, deep learning neural networks, deep learning nlp, deep learning nyu, deep learning numericals, deep learning networks, deep learning neural network tutorial, deep learning nlp python, deep learning nvidia, deep learning on macbook air m1, deep learning object detection, deep learning overview, deep learning on cloud, deep learning on amd gpu, deep learning or machine learning, deep learning on fpga, deep learning on laptop, o que é deep learning, deep learning playlist, deep learning python, deep learning projects in python,

This AI Learned Physics...But How Good Is It? ⚛

❤️ Check out Perceptilabs and sign up for a free demo here: https://ift.tt/2WIdXXn 📝 The paper "High-order Differentiable Autoencoder for Nonlinear Model Reduction" is available here: https://ift.tt/3pK86jQ 🙏 We would like to thank our generous Patreon supporters who make Two Minute Papers possible: Aleksandr Mashrabov, Alex Haro, Andrew Melnychuk, Angelos Evripiotis, Benji Rabhan, Bryan Learn, Christian Ahlin, Eric Haddad, Eric Martel, Gordon Child, Ivo Galic, Jace O'Brien, Javier Bustamante, John Le, Jonas, Kenneth Davis, Klaus Busse, Lorin Atzberger, Lukas Biewald, Matthew Allen Fisher, Mark Oates, Michael Albrecht, Michael Tedder, Nikhil Velpanur, Owen Campbell-Moore, Owen Skarpness, Rajarshi Nigam, Ramsey Elbasheer, Steef, Taras Bobrovytsky, 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/2icTBUb Thumbnail background design: Felícia Zsolnai-Fehér - http://felicia.hu Meet and discuss your ideas with other Fellow Scholars on the Two Minute Papers Discord: https://ift.tt/2TnVBd3 Károly Zsolnai-Fehér's links: Instagram: https://ift.tt/2KBCNkT Twitter: https://twitter.com/twominutepapers Web: https://ift.tt/1NwkG9m

I went to an AI Art Festival in Geneva (AiiA Festival Trip Report)

#aiia #ai #art A trip report from the AiiA Festival in Geneva organized by the ImpactAI foundation. OUTLINE: 0:00 - Intro 1:50 - Laura Tocmacov: The Festival 4:10 - Timothy O'Hear: The Tech 6:50 - Jonathan O'Hear: The Robot 11:50 - Cléa Chopard: The Artist 17:45 - Final Words Website: https://ift.tt/3GlIr73 Links: TabNine Code Completion (Referral): http://bit.ly/tabnine-yannick YouTube: https://www.youtube.com/c/yannickilcher Twitter: https://twitter.com/ykilcher Discord: https://ift.tt/3dJpBrR BitChute: https://ift.tt/38iX6OV Minds: https://ift.tt/37igBpB Parler: https://ift.tt/38tQU7C LinkedIn: https://ift.tt/3qcgOFy BiliBili: https://ift.tt/3mfyjkW 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/2DuKOZ3 Patreon: https://ift.tt/390ewRH Bitcoin (BTC): bc1q49lsw3q325tr58ygf8sudx2dqfguclvngvy2cq Ethereum (ETH): 0x7ad3513E3B8f66799f507Aa7874b1B0eBC7F85e2 Litecoin (LTC): LQW2TRyKYetVC8WjFkhpPhtpbDM4Vw7r9m Monero (XMR): 4ACL8AGrEo5hAir8A9CeVrW8pEauWvnp1WnSDZxW7tziCDLhZAGsgzhRQABDnFy8yuM9fWJDviJPHKRjV4FWt19CJZN9D4n

Tuesday, October 26, 2021

INPUT( ) | FUNCTION TYPE CASTING IN PYTHON PYTHON CRASH COURSE VIDEO 04 | PYTHON PROGRAMMING

Visualizing autoencoders - Made with TensorFlow.js

Meet Doug Duhaime, a software engineer and professor at Yale University who has been exploring autoencoders in TensorFlow.js. See how he creates impressive transformations of high dimensional space to 2D space, or provides demonstrations to envision the mechanics of machine learning to educate students around dimensionality reduction. Doug has been using TensorFlow.js to demonstrate what autoencoders are able to learn after being trained on classic data sets such as MNIST and Celeb-A to walk the learnt 2 dimensional latent space and visualize new faces never seen before all in realtime in the browser. Try it for yourself: Autoencoders by Douglas Duhaime → https://goo.gle/2XvSlkE 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 product: TensorFlow - TensorFlow JS, TensorFlow - General; fullname: Jason Mayes;

Monday, October 25, 2021

TYPE CASTING IN PYTHON PYTHON CRASH COURSE VIDEO 04 | PYTHON PROGRAMMING

Sunday, October 24, 2021

Symbolic Knowledge Distillation: from General Language Models to Commonsense Models (Explained)

#gpt3 #knowledge #symbolic Symbolic knowledge models are usually trained on human-generated corpora that are cumbersome and expensive to create. Such corpora consist of structured triples of symbolic knowledge. This paper takes a different approach and attempts to generate such a corpus by prompting GPT-3. Results show that clever prompting, combined with targeted small critic models trained on human ratings can outperform both human-generated data, as well as the teacher model (GPT-3) itself. The results of this paper give a general recipe for automatically building corpora for various NLP tasks by extracting samples from large language models. OUTLINE: 0:00 - Intro & Overview 2:30 - Sponsor: Weights & Biases 4:15 - Commonsense Knowledge Graphs 7:50 - ATOMIC dataset 10:00 - Generating the corpus from a model 13:00 - Prompting GPT-3 15:30 - Generating Events 18:40 - Generating Inferences 23:00 - Evaluating the created dataset 26:45 - Introducing the critic 31:25 - Using the critic to filter the data 36:30 - Training a student on the generated data 41:00 - Key Findings 44:45 - Comments & Conclusion Paper: https://ift.tt/3APc9Nu Code & Corpus: https://ift.tt/3noXUdJ Sponsor: Weights & Biases https://wandb.com https://ift.tt/3Bdcz0x Abstract: The common practice for training commonsense models has gone from-human-to-corpus-to-machine: humans author commonsense knowledge graphs in order to train commonsense models. In this work, we investigate an alternative, from-machine-to-corpus-to-machine: general language models author these commonsense knowledge graphs to train commonsense models. Our study leads to a new framework, Symbolic Knowledge Distillation. As with prior art in Knowledge Distillation (Hinton et al., 2015), our approach uses larger models to teach smaller models. A key difference is that we distill knowledge symbolically-as text-in addition to the neural model. We also distill only one aspect-the commonsense of a general language model teacher, allowing the student to be a different type, a commonsense model. Altogether, we show that careful prompt engineering and a separately trained critic model allow us to selectively distill high-quality causal commonsense from GPT-3, a general language model. Empirical results demonstrate that, for the first time, a human-authored commonsense knowledge graph is surpassed by our automatically distilled variant in all three criteria: quantity, quality, and diversity. In addition, it results in a neural commonsense model that surpasses the teacher model's commonsense capabilities despite its 100x smaller size. We apply this to the ATOMIC resource, and share our new symbolic knowledge graph and commonsense models. Authors: Peter West, Chandra Bhagavatula, Jack Hessel, Jena D. Hwang, Liwei Jiang, Ronan Le Bras, Ximing Lu, Sean Welleck, Yejin Choi Links: TabNine Code Completion (Referral): http://bit.ly/tabnine-yannick YouTube: https://www.youtube.com/c/yannickilcher Twitter: https://twitter.com/ykilcher Discord: https://ift.tt/3dJpBrR BitChute: https://ift.tt/38iX6OV Minds: https://ift.tt/37igBpB Parler: https://ift.tt/38tQU7C LinkedIn: https://ift.tt/3qcgOFy BiliBili: https://ift.tt/3mfyjkW 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/2DuKOZ3 Patreon: https://ift.tt/390ewRH Bitcoin (BTC): bc1q49lsw3q325tr58ygf8sudx2dqfguclvngvy2cq Ethereum (ETH): 0x7ad3513E3B8f66799f507Aa7874b1B0eBC7F85e2 Litecoin (LTC): LQW2TRyKYetVC8WjFkhpPhtpbDM4Vw7r9m Monero (XMR): 4ACL8AGrEo5hAir8A9CeVrW8pEauWvnp1WnSDZxW7tziCDLhZAGsgzhRQABDnFy8yuM9fWJDviJPHKRjV4FWt19CJZN9D4n

Tutorial | Anomaly Detection | Local Outlier Factor | Coding Session 1/2

This is a snippet of Deloitte's crash course (40 videos) on AI, Machine Learning and Deep Learning: https://rainmakers.talentlms.com/catalog/info/id:125 It is also a snippet from a 'Master in Data Science Course', a 30hrs, AI, Machine Learning and Deep Learning (275 videos): https://www.udemy.com/course/machine-learning-become-expert-full-course-31hrs/?referralCode=6AF072FA748271AAC9A1 This is a complete course including all math details and with coding exercises - no prerequisites are required

Saturday, October 23, 2021

AI-based Business Intelligence and Automation Solutions Improve Business Process Efficiency

AIOTIZE is a company that is working closely towards Artificial Intelligence and Machine Learning to provide business intelligence for enterprises and governments. Check out the full conversation with Aiotize: Chapters: 00:00 Introduction 01:33 Type of solutions and products offered by AIOTIZE 03:36 Drone automation platform – IOX 14:06 Applications and working of the AI Engine "Cognixa" 14:59 Drones and Rovers - Which is the best option for data collection 16:38 Kind of technology and platform used to build the business solutions by Aiotize 17:53 Challenges in developing and deploying a solution 19:25 Future and Market for AI and Data Analytics 21:25 Future plans of the company ------------------------------------------------------------------------------------------------------------------------- Subscribe to our Newsletter to never miss an update on CircuitDigest: http://eepurl.com/dJ5xqU For NodeMCU based tutorials, please visit https://circuitdigest.com/nodemcu-esp8266-projects Find the latest electronics industry news covering new electronics components releases in various electronics domains such as embedded, power electronics, analog, digital, IoT, and Automotive industries: https://circuitdigest.com/news ------------------------------------------------------------------------------------------------------------------------- Connect with CircuitDigest: 👉 Website: https://circuitdigest.com/ 👉 Facebook: https://www.facebook.com/circuitdigest 👉 Twitter: https://twitter.com/CircuitDigest 👉 Instagram: https://www.instagram.com/circuit_digest 👉 Pinterest: https://in.pinterest.com/circuitdigest 👉 LinkedIn: https://www.linkedin.com/company/circuit-digest/ Like, Share, and Subscribe to our YouTube Channel: https://www.youtube.com/Circuitdigest -------------------------------------------------------------------------------------------------------------------------

Explore Machine Learning Models with Explainable AI: Challenge Lab || Qwiklabs || GSP324

COPY COMMANDS FROM HERE : https://docs.google.com/document/d/1I-_cNp4xcXBPLZCo8FGy9x4ccAvPDpwmhYBVOIpINGA/edit?usp=sharing

What is Machine Learning? 2022 (Tech With Sam)

Machine Learning is a subset of AI that describes the specific techniques used for training models to learn tasks, using data. You’ll hear the word ‘model’ thrown around a lot in this context, but it simply refers to the output of a machine learning process, which ‘models’ some real world process. For example, a weather model trained on years of weather data models how weather patterns work in the real world. This model can then use current weather data to simulate the following week’s weather, and report back what it expects the weather to be like in the coming days. #machinelearning #artificialintelligence #techwithsam machine learning algorithms machine learning meaning machine learning engineer machine learning tutorial machine learning pdf machine learning jobs machine learning and artificial intelligence machine learning applications machine learning and data science machine learning algorithms pdf machine learning and data analytics machine learning and deep learning machine learning and artificial intelligence courses a machine learning does not understand a machine learning solution a machine learning technique that helps in detecting a machine learning approach for micro-credit scoring machine learning books machine learning basics machine learning by andrew ng machine learning bootcamps machine learning basics pdf machine learning benefits machine learning books for beginners machine learning basic interview questions b tech machine learning wx+b machine learning w&b machine learning iiit b machine learning appendix b machine learning project checklist b tech machine learning syllabus nagaraj b machine learning b. azure machine learning studio machine learning course machine learning companies machine learning certification machine learning career machine learning classification machine learning companies in nigeria machine learning classification algorithms machine learning course free c machine learning framework c sharp machine learning c programming machine learning c sharp machine learning library c value machine learning c/c++ machine learning c index machine learning c elegans machine learning machine learning definition machine learning datasets machine learning data science machine learning definition and examples machine learning degree machine learning developer machine learning developer salary d machine learning algorithms deepak d machine learning r&d machine learning wave machine learning d&d machine learning d lang machine learning d e shaw machine learning d-separation in machine learning machine learning engineer salary machine learning engineer salary in nigeria machine learning examples machine learning engineer jobs machine learning experts machine learning engineer salary uk machine learning engineer salary in canada e machine learning algorithms e machine learning techniques e commerce machine learning e-commerce machine learning projects e commerce machine learning case study e-commerce machine learning examples weinan e machine learning e uci machine learning repository machine learning for beginners machinekopics machine learning requirements machine learning remote jobs machine learning research papers 2021 machine learning researcher machine learning research papers 2020 machine learning research papers pdf r machine learning packages r machine learning book r machine learning reddit r machine learning projects pdf r machine learning cheat sheet r machine learning course r machine learning models machine learning salary machine learning salary in nigeria machine learning skills machine learning software machine learning salary in canada machine learning steps machine learning scientist machine learning scholarship is machine learning hard is machine learning a good career is machine learning data science is machine learning same as artificial intelligence is machine learning is machine learning ai is machine learning easy is machine learning artificial intelligence machine learning techniques machine learning tutorial pdf machine learning tools machine learning types machine learning textbook machine learning tutorialspoint machine learning topics t test machine learning t-sne machine learning t. mitchell machine learning at&t machine learning t test machine learning python t mobile machine learning t sql machine learning machine learning udemy machine learning uses machine learning undergraduate projects machine learning udacity machine learning use cases machine learning upwork machine learning university u-net machine learning u washington machine learning u toronto machine learning wolfram u machine learning umap machine learning uchicago machine learning itunes u jithm

Tutorial | Anomaly Detection | Local Outlier Factor | Coding Session 1/2

Friday, October 22, 2021

What is Machine Learning? 2022 (Tech With Sam)

Simulating 800 Metric Tons of Glaciers! 🌊

❤️ Check out Perceptilabs and sign up for a free demo here: https://ift.tt/2WIdXXn 📝 The paper "A glacier–ocean interaction model for tsunami genesis due to iceberg calving" is available here: https://ift.tt/3Gf59gQ 🙏 We would like to thank our generous Patreon supporters who make Two Minute Papers possible: Aleksandr Mashrabov, Alex Haro, Andrew Melnychuk, Angelos Evripiotis, Benji Rabhan, Bryan Learn, Christian Ahlin, Eric Haddad, Eric Martel, Gordon Child, Ivo Galic, Jace O'Brien, Javier Bustamante, John Le, Jonas, Kenneth Davis, Klaus Busse, Lorin Atzberger, Lukas Biewald, Matthew Allen Fisher, Mark Oates, Michael Albrecht, Nikhil Velpanur, Owen Campbell-Moore, Owen Skarpness, Rajarshi Nigam, Ramsey Elbasheer, Steef, Taras Bobrovytsky, 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/2icTBUb Thumbnail background image credit: https://ift.tt/3AZWIlW Thumbnail background design: Felícia Zsolnai-Fehér - http://felicia.hu Meet and discuss your ideas with other Fellow Scholars on the Two Minute Papers Discord: https://ift.tt/2TnVBd3 Károly Zsolnai-Fehér's links: Instagram: https://ift.tt/2KBCNkT Twitter: https://twitter.com/twominutepapers Web: https://ift.tt/1NwkG9m

Thursday, October 21, 2021

Tutorial System in Learning Activities Through ML-Based Chatbot App in Pharmacology Education

Title : Tutorial System in Learning Activities Through Machine Learning-Based Chatbot Applications in Pharmacology Education ID Paper : 48 Authors : Muhammad Rizki Fonna and Dwi Hendratmo Widyantoro ICAICTA 2021 is the 8th International Conference on Advanced Informatics: Concepts, Theory and Applications, which held in September 29-30, 2021 Website : https://aicenter.itb.ac.id/icaicta-2021/ #ICAICTA #MachineLearning #DeepLearning #ArtificialIntelligence #AI #ML

PRINT ( ) FUNCTION | .PY EXTENSION | PYTHON CRASH COURSE | VIDEO 01 | PYTHON PROGRAMMING

PYCHARM COMPLETE INSTALLATION https://youtu.be/pwEt50n2K1c Hey everyone This is Ujjwal kapil B.tech 2nd year Ai and Ml this we are starting are series in which we are covering every basic concept of Python programming Language I assure you that if you continue ths series with me you will be able to solve basic question of python and we are also going to do live question practice of python so what you have to do is just subscribe the channel so that you can get every video and update on time Join us on telegram Group https://t.me/Ujjwalkapil09 ----------------------------------------------------------------------------------------------------- UTU site--https://uktech.ac.in/ All weekly episode are available on Spotify https://open.spotify.com/episode/7FlM... Jiosaavn https://www.jiosaavn.com/shows/the-sp... google podcast https://www.google.com/podcasts?feed=... anchor.fm https://anchor.fm/ujjwal-kapil/episod... Website by me- https://ujjwalkapil09.github.io/roses... Connect with me on LinkedIn- https://www.linkedin.com/in/ujjwal-ka... follow me on Instagram https://www.instagram.com/ujjwal091102/ Facebook -https://www.facebook.com/ujjwal.kapil.90 Mic I use -----https://amzn.to/3jcV0Yb Laptop --- https://amzn.to/3vzmpZD phone used while recording-- https://amzn.to/2XmBeln #python #pythonprogramming #pythontutorial #pythontutorialforbeginners #pythontutorialforbeginnersinhindi #ujjwalkapil #artificial intelligence,#machine learning,what is artificial intelligence,artificial intelligence tutorial,artificial intelligence and machine learning,machine learning vs artificial intelligence,artificial intelligence tutorial for beginners,machine learning tutorial,simplilearn artificial intelligence,artificial intelligence explained,artificial intelligence course,artificial intelligence edureka,artificial intelligence vs machine learning vs deep learning PANTNAGAR govind ballabh pant institute of engineering and technology pauri pauri garwal govind ballabh pant university of agriculture and technology

I took a Swiss train and it was awesome! Train Seat Review - SBB InterCity 1 - Geneva to St. Gallen

#sbb #seatreview #travel A friendly parody of Travel Vloggers and Airplane Seat Reviews :) No, SBB did not pay me for this (but they should ;) ) Links: TabNine Code Completion (Referral): http://bit.ly/tabnine-yannick YouTube: https://www.youtube.com/c/yannickilcher Twitter: https://twitter.com/ykilcher Discord: https://ift.tt/3dJpBrR BitChute: https://ift.tt/38iX6OV Minds: https://ift.tt/37igBpB Parler: https://ift.tt/38tQU7C LinkedIn: https://ift.tt/3qcgOFy BiliBili: https://ift.tt/3mfyjkW 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/2DuKOZ3 Patreon: https://ift.tt/390ewRH Bitcoin (BTC): bc1q49lsw3q325tr58ygf8sudx2dqfguclvngvy2cq Ethereum (ETH): 0x7ad3513E3B8f66799f507Aa7874b1B0eBC7F85e2 Litecoin (LTC): LQW2TRyKYetVC8WjFkhpPhtpbDM4Vw7r9m Monero (XMR): 4ACL8AGrEo5hAir8A9CeVrW8pEauWvnp1WnSDZxW7tziCDLhZAGsgzhRQABDnFy8yuM9fWJDviJPHKRjV4FWt19CJZN9D4n

Wednesday, October 20, 2021

INTRODUCTION TO PYTHON | SYLLABUS OVERVIEW | CBSE CLASS 12 | FOR BEGINNERS | let's learn python

Tutorial System in Learning Activities Through ML-Based Chatbot App in Pharmacology Education

PRINT ( ) FUNCTION | .PY EXTENSION | PYTHON CRASH COURSE | VIDEO 01 | PYTHON PROGRAMMING

Classifying satellite imagery - Made with TensorFlow.js

Meet Sean McGee, a software developer at Esri UK who helps customers solve real-world problems with GIS (Geographical Information Systems) and machine learning. Recently he has been using TensorFlow.js with satellite imagery to recognize objects across geographical regions client side in the browser. Try it for yourself: Github Repository → https://goo.gle/3AuMxGy GIS Satellite Imagery by Sean McGee → https://goo.gle/3lLZk2y 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 product: TensorFlow - TensorFlow JS, TensorFlow - General; fullname: Jason Mayes;

[ML News] Microsoft trains 530B model | ConvMixer model fits into single tweet | DeepMind profitable

#mlnews #turingnlg #convmixer Your latest upates on what's happening in the Machine Learning world. OUTLINE: 0:00 - Intro 0:16 - Weights & Biases raises on 1B valuation (sponsored) 2:30 - Microsoft trains 530 billion parameter model 5:15 - StyleGAN v3 released 6:45 - A few more examples may be worth billions of parameters 8:30 - ConvMixer fits into a tweet 9:45 - Improved VQGAN 11:25 - William Shatner AI chats about his life 12:35 - Google AI pushes material science 14:10 - Gretel AI raises 50M for privacy protection 16:05 - DeepMind's push into ML for biology 19:00 - Schmidhuber laudates Kunihiko Fukushima for Bower Award 21:30 - Helpful Things 22:25 - Mosaic ML out of stealth mode 23:55 - First German self-driving train 24:45 - Ex-Pentagon Chief: China has already won 26:25 - DeepMind becomes profitable References: Microsoft Trains 530B Parameter Model https://ift.tt/3DprzKa StyleGAN 3 Code Released https://ift.tt/3oUOwRw https://ift.tt/3oOQnr7 https://ift.tt/3lVSvvh When do labels help? https://ift.tt/3DVzb7u ml_paper.bruh https://ift.tt/3jmQI0v Improved VQGAN https://ift.tt/3aUMEjv William Shatner "AI" & Storyfile https://ift.tt/3piXloi https://ift.tt/2Zbjbzm GoogleAI Finds Complex Metal Oxides https://ift.tt/3BntEWw GretelAI raises 50M Series B https://ift.tt/3BmB4t6 https://gretel.ai/ https://ift.tt/3G0UvKG DeepMind's Push in ML for Bio https://ift.tt/3lbqI9W https://ift.tt/2Yphlun Kunihiko Fukushima wins Bower Award: Schmidhuber Congratulates https://ift.tt/2Z4SVqJ https://www.youtube.com/watch?v=ysOw6lNWx2o Helpful Things https://ift.tt/3vuLYea https://ift.tt/3AXdL87 https://ift.tt/3mWp2Au https://ift.tt/3BYNIik https://ift.tt/3plxEUq MosaicML out of Stealth Mode https://ift.tt/3vHyNqx https://ift.tt/3E2LQFV https://ift.tt/2YMjOih https://ift.tt/3BZeJlL https://ift.tt/3pzB85R Germany's first self-driving train https://ift.tt/3v5e93g Ex-Pentagon Chief: China has already won tech war https://ift.tt/2YAtwnZ DeepMind becomes profitable https://ift.tt/3AhNZuV Links: TabNine Code Completion (Referral): http://bit.ly/tabnine-yannick YouTube: https://www.youtube.com/c/yannickilcher Twitter: https://twitter.com/ykilcher Discord: https://ift.tt/3dJpBrR BitChute: https://ift.tt/38iX6OV Minds: https://ift.tt/37igBpB Parler: https://ift.tt/38tQU7C LinkedIn: https://ift.tt/3qcgOFy BiliBili: https://ift.tt/3mfyjkW 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/2DuKOZ3 Patreon: https://ift.tt/390ewRH Bitcoin (BTC): bc1q49lsw3q325tr58ygf8sudx2dqfguclvngvy2cq Ethereum (ETH): 0x7ad3513E3B8f66799f507Aa7874b1B0eBC7F85e2 Litecoin (LTC): LQW2TRyKYetVC8WjFkhpPhtpbDM4Vw7r9m Monero (XMR): 4ACL8AGrEo5hAir8A9CeVrW8pEauWvnp1WnSDZxW7tziCDLhZAGsgzhRQABDnFy8yuM9fWJDviJPHKRjV4FWt19CJZN9D4n

Tuesday, October 19, 2021

Women in Machine Learning Symposium 2021 livestream

The Women in ML Symposium is a safe space for women and gendered minorities to come together and speak freely about career development through knowledge sharing and networking. Everyone is welcome to attend! This event focuses on empowering women to advance their careers, join open source communities, seek out leadership opportunities, and how we all can support gender equity in the ML community. 00:00 Welcome 1:53 Starting soon 10:25 Introduction 12:39 Why diversity matters in Machine Learning communities 24:35 Making OSS Machine Learning communities more diverse 41:40 Fireside chat - From being the only woman in the room to empowering the next generation 1:16:19 Coffee break 1:29:00 How to get started in Machine Learning 2:26:06 Key takeaways Watch more: Watch all the Women in ML Symposium Sessions → https://goo.gle/WiML-allsessions Subscribe to TensorFlow → https://goo.gle/TensorFlow #WIMLsymposium product: ML Kit - General; event: Women in ML Symposium 2021; re_ty: Livestream;

INTRODUCTION TO PYTHON | SYLLABUS OVERVIEW | CBSE CLASS 12 | FOR BEGINNERS | let's learn python

Sunday, October 17, 2021

How to Learn Deep Learning in 2022 - A Self Study Guide

A complete End to End Self study Guide for building your own curriculum for Deep Learning in 2022 . Subscribe to our channel for more quality content on Data Science, Machine Learning and Deep Learning. Checkout our Playlist on Youtube: Deep learning with Tensorflow : https://www.youtube.com/watch?v=l8HaRZWHmfg&list=PL3Sk77w7CQs_VrXLP_Kmj3ufmhehMrfHp Deep Learning with Pytorch : https://www.youtube.com/watch?v=X9p9STSO23U&list=PL3Sk77w7CQs91pSHCH18eMzD8BJ_lvK4m Linear Algebra Tutorials: https://www.youtube.com/watch?v=035zPwY8BDQ&list=PL3Sk77w7CQs9c6GhauRPhKd4HPAM7E5Vi Happy Learning

Saturday, October 16, 2021

This Image Is Fine. Completely Fine. 🤖

❤️ Check out Lambda here and sign up for their GPU Cloud: https://ift.tt/35NkCT7 📝 The paper "The Sensory Neuron as a Transformer: Permutation-Invariant Neural Networks for Reinforcement Learning" is available here: https://ift.tt/3hbY45Z 🙏 We would like to thank our generous Patreon supporters who make Two Minute Papers possible: Aleksandr Mashrabov, Alex Haro, Andrew Melnychuk, Angelos Evripiotis, Benji Rabhan, Bryan Learn, Christian Ahlin, Eric Haddad, Eric Martel, Gordon Child, Ivo Galic, Jace O'Brien, Javier Bustamante, John Le, Jonas, Kenneth Davis, Klaus Busse, Lorin Atzberger, Lukas Biewald, Matthew Allen Fisher, Mark Oates, Michael Albrecht, Nikhil Velpanur, Owen Campbell-Moore, Owen Skarpness, Rajarshi Nigam, Ramsey Elbasheer, Steef, Taras Bobrovytsky, 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/2icTBUb Thumbnail background design: Felícia Zsolnai-Fehér - http://felicia.hu Meet and discuss your ideas with other Fellow Scholars on the Two Minute Papers Discord: https://ift.tt/2TnVBd3 Károly Zsolnai-Fehér's links: Instagram: https://ift.tt/2KBCNkT Twitter: https://twitter.com/twominutepapers Web: https://ift.tt/1NwkG9m

Friday, October 15, 2021

What is machine learning | ML | Beginners tutorial | AI vs ML vs Machine Learning | timepasscoders

What is machine learning | ML | Beginners tutorial | AI vs ML vs Machine Learning | timepasscoders Hlo Guys welcome to TimePass Coders Connect with us on instagram https://www.instagram.com/timepasscoders/ Follow us on twitter you can connect to us on twitter https://twitter.com/CodersPass?s=09 This video will help for the following questions : what is machine learning in hindi, what is machine learning in tamil, what is machine learning in telugu, what is machine learning and artificial intelligence, what is machine learning and how does it work, what is machine learning in english, what is machine learning in malayalam, what is machine learning and deep learning, what is machine learning and data science, what is machine learning and ai, what is machine learning algorithm, what is machine learning and artificial intelligence in hindi, what is machine learning basics, what is machine learning benefits, what is machine learning code with harry, what is machine learning classification, what is machine learning deep learning and artificial intelligence, what is machine learning deep learning, what is machine learning deep learning and ai, what is machine learning data, what is machine learning examples, what is machine learning explain, what is machine learning give example, what is machine learning model How to get started with programming | How to start coding | Guide | beginner tutorial | Road map | timepasscoders In this video we are going to see how we can start coding This video is the answer for the following questions Which language to learn Which field to choose in programming Which programming language to learn first Which coding language to start coding with Which field to choose Web Development Wendevelopment Aiml Ai Ml Artificial intelligence Machine learning deep learning Deep learning Ethical hacking Data science Which one to choose Which have future How to start coding Which is easy to start with How to code Beginner guide

Thursday, October 14, 2021

What is machine learning | ML | Beginners tutorial | AI vs ML vs Machine Learning | timepasscoders

Wednesday, October 13, 2021

Announcing Google's Machine Learning Virtual Community Day

Whether you're new to AI & ML or a pro developer, we invite you to join Google's virtual Machine Learning Community Day on Tuesday November 9th. * Learn how to build and deploy ML models across the cloud, web, browser, mobile and microcontrollers. * Discover how Google’s frameworks and tools help push state-of-the-art research in ML and artificial intelligence. * Watch how the community builds solutions to real-world problems with ML, AI and deep learning. * Finally, learn the latest on TensorFlow, JAX, and more. See you there! Learn more → https://goo.gle/mlcommunityday-yt Subscribe to the TensorFlow channel → https://goo.gle/TensorFlow #MLCommunityDay product: TensorFlow - General; event: ML Community Day 2021;

Tuesday, October 12, 2021

Accessible Data science with Hal9 - Made with TensorFlow.js

Javier Luraschi, creator of Hal9, is using his platform to make data science more accessible for developers everywhere. Hal9 allows you to explore data sets by using TensorFlow.js in the browser. See Hal9 in action as he demonstrates how you can instantly visualize data from a whole bunch of sources, refine it, and then apply pre-made models for things like sentiment analysis to further process the input data to gain extra insights. We also dive into LSTMs for time series data, and image classification to better interpret datasets containing images to understand what types of imagery make up your dataset and more! Try it for yourself: Hal9 by Javier Luraschi → https://goo.gle/3nIByWr 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 Have a question? Ask it on the TensorFlow Forum and tag with “TFJS” → https://ift.tt/2YRxglo product: TensorFlow - TensorFlow JS, TensorFlow - General; fullname: Jason Mayes;

Finally, Beautiful Virtual Scenes…For Less! ☀️

❤️ Check out Weights & Biases and sign up for a free demo here: https://ift.tt/2S5tXnb ❤️ Their mentioned post is available here: https://ift.tt/3ruAL9V 📝 The paper "DONeRF: Towards Real-Time Rendering of Compact Neural Radiance Fields using Depth Oracle Networks" is available here: https://ift.tt/3y4K2sZ Meet and discuss your ideas with other Fellow Scholars on the Two Minute Papers Discord: https://ift.tt/2TnVBd3 🙏 We would like to thank our generous Patreon supporters who make Two Minute Papers possible: Aleksandr Mashrabov, Alex Haro, Andrew Melnychuk, Angelos Evripiotis, Benji Rabhan, Bryan Learn, Christian Ahlin, Eric Haddad, Eric Martel, Gordon Child, Ivo Galic, Jace O'Brien, Javier Bustamante, John Le, Jonas, Kenneth Davis, Klaus Busse, Lorin Atzberger, Lukas Biewald, Matthew Allen Fisher, Mark Oates, Michael Albrecht, Nikhil Velpanur, Owen Campbell-Moore, Owen Skarpness, Rajarshi Nigam, Ramsey Elbasheer, Steef, Taras Bobrovytsky, 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/2icTBUb Thumbnail background image credit: https://ift.tt/3arVFQW Thumbnail background design: Felícia Zsolnai-Fehér - http://felicia.hu Károly Zsolnai-Fehér's links: Instagram: https://ift.tt/2KBCNkT Twitter: https://twitter.com/twominutepapers Web: https://ift.tt/1NwkG9m

Saturday, October 9, 2021

Simulating Ships, Oceans, And Everything! 🌊

❤️ Check out Perceptilabs and sign up for a free demo here: https://ift.tt/2WIdXXn 📝 The paper "Ships, Splashes, and Waves on a Vast Ocean" is available here: https://ift.tt/2YBZXTr 🙏 We would like to thank our generous Patreon supporters who make Two Minute Papers possible: Aleksandr Mashrabov, Alex Haro, Andrew Melnychuk, Angelos Evripiotis, Benji Rabhan, Bryan Learn, Christian Ahlin, Eric Haddad, Eric Martel, Gordon Child, Ivo Galic, Jace O'Brien, Javier Bustamante, John Le, Jonas, Kenneth Davis, Klaus Busse, Lorin Atzberger, Lukas Biewald, Matthew Allen Fisher, Mark Oates, Michael Albrecht, Nikhil Velpanur, Owen Campbell-Moore, Owen Skarpness, Ramsey Elbasheer, Steef, Taras Bobrovytsky, 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/2icTBUb Thumbnail background design: Felícia Zsolnai-Fehér - http://felicia.hu Meet and discuss your ideas with other Fellow Scholars on the Two Minute Papers Discord: https://ift.tt/2TnVBd3 Károly Zsolnai-Fehér's links: Instagram: https://ift.tt/2KBCNkT Twitter: https://twitter.com/twominutepapers Web: https://ift.tt/1NwkG9m

Thursday, October 7, 2021

Webinar on Artificial Intelligence and Machine Learning - Emerging trends & Applications| BGSB UNIV

ORGANIZED BY DEPARTMENT OF INFORMATION TECHNOLOGY BABA GHULAM SHAH BADSHAH UNIVERSITY RAJOURI - JAMMU & KASHMIR - 185234 Established by Govt. of J&K , Recognised by UGC under section 2(F) & 12(B) https://www.bgsbu.ac.in/ RESOURCE PERSON: Dr. D Doreen Robin M.E., Ph.D Founder & Director, CIRF E Mail: doreencirf@gmail.com Mobile No: 9003021355 www.cirf.co.in

Real time motion capture for VTubers - Made with TensorFlow.js

Meet Richard Yee and his avatar as he explains how he’s used TensorFlow.js pose and face models to create real time motion capture for VTubers in the browser and even play an online theremin. Try it for yourself: Kalido face demo → https://goo.gle/3CogV5S Theremin demo → https://theremin.app/ 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 product: TensorFlow - TensorFlow JS, TensorFlow - General; fullname: Jason Mayes;

[ML News] DeepMind does Nowcasting | The Guardian's shady reporting | AI finishes Beethoven's 10th

#deepmind #nowcasting #machinelearning Your holy update on what's new in the Machine Learning world. OUTLINE: 0:00 - Intro 0:30 - DeepMind tackles Nowcasting 3:30 - The Guardian's shady reporting on TruthfulQA 6:15 - Stochastic training not necessary for generalization 7:35 - Google AI's efficient partitioning of road networks 9:15 - MiniHack Reinforcement Learning Environment 10:45 - Plato XL 11B dialog model 11:35 - AI finishes Beethoven's 10th Symphony 13:10 - AI casts doubt on painting authenticity 15:55 - ShadowDragon social media surveillance 18:45 - Helpful Libraries 25:20 - Samsung to copy-paste brains onto chips References: DeepMind improves Nowcasting https://ift.tt/3kPBDWw https://ift.tt/3undgT6 https://ift.tt/2WrnEwL https://ift.tt/3uPyMAc The Guardian's shady reporting on TruthfulQA https://ift.tt/3agj5IN Stochastic Training is Not Necessary for Generalization https://ift.tt/3A4VBRo Google AI - Efficient Partitioning of Road Networks https://ift.tt/39QNnS7 MiniHack Reinforcement Learning Environment https://ift.tt/2Ysdo7Q Baidu PLATO-XL 11B Dialog Model https://ift.tt/3olyJuK AI finishes Beethoven's 10th Symphony https://ift.tt/3mfGiAG AI casts doubt on paining authenticity https://ift.tt/2Y0XC3S https://ift.tt/3mz5emx https://ift.tt/3mwcXll https://ift.tt/3oLQ00x ShadowDragon Social Media Surveillance https://ift.tt/2XM4cv2 https://ift.tt/3EI0Nhx Helpful Libraries / Datasets https://ift.tt/3nYC4zU https://ift.tt/3Bscp6A https://ift.tt/3Af2OOU https://ift.tt/3FoXNqM https://ift.tt/3uq0RxX https://ift.tt/3iHUd1n https://ift.tt/3iB4lZJ https://ift.tt/3ahi4Ai https://ift.tt/3oHDvTE https://ift.tt/3lfuAXf https://ift.tt/3mpJNVh https://ift.tt/3uQk0ZR https://ift.tt/3DpVUZj https://ift.tt/3BoP716 https://ift.tt/3adOMCA Samsung Method to copy paste brain onto chip https://ift.tt/3i9rpOK Links: TabNine Code Completion (Referral): http://bit.ly/tabnine-yannick YouTube: https://www.youtube.com/c/yannickilcher Twitter: https://twitter.com/ykilcher Discord: https://ift.tt/3dJpBrR BitChute: https://ift.tt/38iX6OV Minds: https://ift.tt/37igBpB Parler: https://ift.tt/38tQU7C LinkedIn: https://ift.tt/3qcgOFy BiliBili: https://ift.tt/3mfyjkW 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/2DuKOZ3 Patreon: https://ift.tt/390ewRH Bitcoin (BTC): bc1q49lsw3q325tr58ygf8sudx2dqfguclvngvy2cq Ethereum (ETH): 0x7ad3513E3B8f66799f507Aa7874b1B0eBC7F85e2 Litecoin (LTC): LQW2TRyKYetVC8WjFkhpPhtpbDM4Vw7r9m Monero (XMR): 4ACL8AGrEo5hAir8A9CeVrW8pEauWvnp1WnSDZxW7tziCDLhZAGsgzhRQABDnFy8yuM9fWJDviJPHKRjV4FWt19CJZN9D4n

Wednesday, October 6, 2021

Grokking: Generalization beyond Overfitting on small algorithmic datasets (Paper Explained)

#grokking #openai #deeplearning Grokking is a phenomenon when a neural network suddenly learns a pattern in the dataset and jumps from random chance generalization to perfect generalization very suddenly. This paper demonstrates grokking on small algorithmic datasets where a network has to fill in binary tables. Interestingly, the learned latent spaces show an emergence of the underlying binary operations that the data were created with. OUTLINE: 0:00 - Intro & Overview 1:40 - The Grokking Phenomenon 3:50 - Related: Double Descent 7:50 - Binary Operations Datasets 11:45 - What quantities influence grokking? 15:40 - Learned Emerging Structure 17:35 - The role of smoothness 21:30 - Simple explanations win 24:30 - Why does weight decay encourage simplicity? 26:40 - Appendix 28:55 - Conclusion & Comments Paper: https://ift.tt/3euNFRK Abstract: In this paper we propose to study generalization of neural networks on small algorithmically generated datasets. In this setting, questions about data efficiency, memorization, generalization, and speed of learning can be studied in great detail. In some situations we show that neural networks learn through a process of “grokking” a pattern in the data, improving generalization performance from random chance level to perfect generalization, and that this improvement in generalization can happen well past the point of overfitting. We also study generalization as a function of dataset size and find that smaller datasets require increasing amounts of optimization for generalization. We argue that these datasets provide a fertile ground for studying a poorly understood aspect of deep learning: generalization of overparametrized neural networks beyond memorization of the finite training dataset. Authors: Alethea Power, Yuri Burda, Harri Edwards, Igor Babuschkin & Vedant Misra Links: TabNine Code Completion (Referral): http://bit.ly/tabnine-yannick YouTube: https://www.youtube.com/c/yannickilcher Twitter: https://twitter.com/ykilcher Discord: https://ift.tt/3dJpBrR BitChute: https://ift.tt/38iX6OV Minds: https://ift.tt/37igBpB Parler: https://ift.tt/38tQU7C LinkedIn: https://ift.tt/3qcgOFy BiliBili: https://ift.tt/3mfyjkW 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/2DuKOZ3 Patreon: https://ift.tt/390ewRH Bitcoin (BTC): bc1q49lsw3q325tr58ygf8sudx2dqfguclvngvy2cq Ethereum (ETH): 0x7ad3513E3B8f66799f507Aa7874b1B0eBC7F85e2 Litecoin (LTC): LQW2TRyKYetVC8WjFkhpPhtpbDM4Vw7r9m Monero (XMR): 4ACL8AGrEo5hAir8A9CeVrW8pEauWvnp1WnSDZxW7tziCDLhZAGsgzhRQABDnFy8yuM9fWJDviJPHKRjV4FWt19CJZN9D4n

Tuesday, October 5, 2021

Grokking Artificial Intelligence Of Things| AI | IoT | Machine Learning | Tutorial | IEMLabs

WHAT IS IOT? The Internet of Things (IoT) is a network of physical objects—“things”—embedded with sensors, software, and other technologies for connecting and sharing data with other devices and systems over the Internet. WHAT IS AIOT? The Artificial Intelligence of Things (AIoT) is the integration of AI technologies with Internet of Things (IoT) infrastructure to create more effective IoT operations, better human-machine engagements, and improve data management and analytics. AI Boosts IOT AI will significantly boost IoT on two fronts. For starters, it affects telemetry data by imbuing sensors with intelligence. Second, artificial intelligence (AI) will be utilized to evaluate the inbound telemetry data stream in real-time or batch mode. It connects to the beginning (devices) and end (analysis) of the IoT spectrum. One Such application is AIOT Smart Cameras. For example, a camera acting as an image sensor will communicate every frame to the IoT system in order to evaluate the feed for certain items. By incorporating AI into the camera device, the frame is only sent when a certain item is recognized. This substantially accelerates the process while sparing the CPU from having to process each frame. The same logic may be used to speech synthesis and other types of telemetry data. AI-enabled sensors are the IoT systems of the future. Smart cameras powered by AI accelerators from Intel, NVIDIA, and Qualcomm will soon be the norm. Another example: Advanced IoT systems will be able to detect abnormalities in real-time by applying deep learning models based on neural networks to incoming sensor telemetry data. When the neural network predicts a major mistake, the malfunctioning equipment may be turned off to avert a catastrophic accident or occurrence. The primary distinction between conventional IoT rules engines and AIoT rules engines is whether they are proactive or reactive. Current IoT systems are meant to respond to an incident, but AIoT systems can identify faults and events in advance. The incorporation of AI into IoT systems offers the promise of predictive maintenance, which will help businesses save millions of dollars in equipment support and maintenance. AIoT (Artificial Intelligence of Things) refers to intelligent, linked systems that can make judgments. Artificial intelligence will enable the most effective use of data generated by IoT components, greatly contributing to their growth. Based on telemetry data, an artificial intelligence-enabled device will be able to govern the entire system of linked, synchronized equipment, manage individual devices, and even make a choice regarding self-repair when some parameters are abnormal. Artificial intelligence in industry is a true game changer: Individual components of a particular factory's machine park will be able to not only send data to humans, signaling that something is wrong, but also automatically take action to eradicate such a threat, owing to this technology. What is Society 5.0? Japan's vision for the future is Society 5.0. It is a super-smart society in which technology such as big data, the Internet of Things (IoT), artificial intelligence (AI), and robotics permeate every sector and social segment. Society 5.0, often known as a "super-smart society," is a vision shared by Japan in 2016 and offered to the Western European world in 2017. (At CeBIT 2017). Download Link : Visual Studio Code – https://code.visualstudio.com/download ❖ To know more visit our Website – https://iemlabs.com ======================================== Follow us on Social Media also: - ❖ Twitter - https://bit.ly/2Lyr36Z ❖ Facebook Page - https://bit.ly/3ng2PfM ❖ Instagram - https://bit.ly/2WgQKva ❖ LinkedIn Page - https://bit.ly/3noDXT9 ❖ Telegram Channel - https://bit.ly/2LtDP6G ❖ Telegram Group - https://bit.ly/37hphjc ========================================== ❖ Please Like, Share and Subscribe our YouTube Channel - https://bit.ly/3ap1EHx ❖ don’t forget to press the Bell Icon #AI #IoT #ML #IEMLabs

Introducing the first Women in Machine Learning Symposium

We’re excited to announce the first Women in Machine Learning Symposium on October 19th! All are welcome to join in and hear from industry leaders as we work toward achieving equity and supporting innovation in Machine Learning communities. Register for the Women in ML Symposium 2021 → https://goo.gle/WIML21-register Learn more about the Women in ML Symposium → https://goo.gle/3u05Zsq Subscribe to TensorFlow → https://goo.gle/TensorFlow #WIMLsymposium product: ML Kit - General; event: Women in ML Symposium 2021; fullname: Joana Carrasqueira; re_ty: Publish;

3D Modeling Without An Artist…Possible? 👩‍🎨

❤️ Check out Fully Connected by Weights & Biases: https://wandb.me/papers 📝 The paper "DAG Amendment for Inverse Control of Parametric Shapes" is available here: https://ift.tt/2SZJRzH Check out Yannic Kilcher's channel here: https://www.youtube.com/c/YannicKilcher/videos 🙏 We would like to thank our generous Patreon supporters who make Two Minute Papers possible: Aleksandr Mashrabov, Alex Haro, Andrew Melnychuk, Angelos Evripiotis, Benji Rabhan, Bryan Learn, Christian Ahlin, Eric Haddad, Eric Martel, Gordon Child, Ivo Galic, Jace O'Brien, Javier Bustamante, John Le, Jonas, Kenneth Davis, Klaus Busse, Lorin Atzberger, Lukas Biewald, Matthew Allen Fisher, Mark Oates, Michael Albrecht, Nikhil Velpanur, Owen Campbell-Moore, Owen Skarpness, Ramsey Elbasheer, Steef, Taras Bobrovytsky, 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/2icTBUb Thumbnail background design: Felícia Zsolnai-Fehér - http://felicia.hu Károly Zsolnai-Fehér's links: Instagram: https://ift.tt/2KBCNkT Twitter: https://twitter.com/twominutepapers Web: https://ift.tt/1NwkG9m