Teaching from Home - Quick Start Guide
By Andrew Ng
Many of us are working to quickly transition from teaching in a live classroom to teaching online
from home. The goal of this document is to help you make that transition quickly and
successfully with a minimum amount of complexity. We will go over the basics, and only the
basics here.
@ArtificialIntelligenceArticles
https://drive.google.com/file/d/1ZPUQTKxkMLPxinT4SHU3_k_p4_Scnqgv/view
@ArtificialIntelligenceArticles
By Andrew Ng
Many of us are working to quickly transition from teaching in a live classroom to teaching online
from home. The goal of this document is to help you make that transition quickly and
successfully with a minimum amount of complexity. We will go over the basics, and only the
basics here.
@ArtificialIntelligenceArticles
https://drive.google.com/file/d/1ZPUQTKxkMLPxinT4SHU3_k_p4_Scnqgv/view
@ArtificialIntelligenceArticles
Blog: https://arstechnica.com/gaming/2020/05/after-watching-50000-hours-of-pac-man-nvidias-ai-generated-a-playable-clone/
Video: https://youtu.be/BYt6r8z6pUY
Video: https://youtu.be/BYt6r8z6pUY
Ars Technica
After watching 50,000 hours of Pac-Man, Nvidia’s AI generated a playable clone
Could a blurry, 128×128 version of a 1980 arcade game change the future of game dev?
Missing Semester
As computer scientists, we know that computers are great at aiding in repetitive tasks. However, far too often, we forget that this applies just as much to our use of the computer as it does to the computations we want our programs to perform. We have a vast range of tools available at our fingertips that enable us to be more productive and solve more complex problems when working on any computer-related problem. Yet many of us utilize only a small fraction of those tools; we only know enough magical incantations by rote to get by, and blindly copy-paste commands from the internet when we get stuck.
This class is an attempt to address this.
We want to teach you how to make the most of the tools you know, show you new tools to add to your toolbox, and hopefully instill in you some excitement for exploring (and perhaps building) more tools on your own. This is what we believe to be the missing semester from most Computer Science curriculum
https://www.youtube.com/watch?v=Z56Jmr9Z34Q&list=PLyzOVJj3bHQuloKGG59rS43e29ro7I57J
As computer scientists, we know that computers are great at aiding in repetitive tasks. However, far too often, we forget that this applies just as much to our use of the computer as it does to the computations we want our programs to perform. We have a vast range of tools available at our fingertips that enable us to be more productive and solve more complex problems when working on any computer-related problem. Yet many of us utilize only a small fraction of those tools; we only know enough magical incantations by rote to get by, and blindly copy-paste commands from the internet when we get stuck.
This class is an attempt to address this.
We want to teach you how to make the most of the tools you know, show you new tools to add to your toolbox, and hopefully instill in you some excitement for exploring (and perhaps building) more tools on your own. This is what we believe to be the missing semester from most Computer Science curriculum
https://www.youtube.com/watch?v=Z56Jmr9Z34Q&list=PLyzOVJj3bHQuloKGG59rS43e29ro7I57J
YouTube
Lecture 1: Course Overview + The Shell (2020)
You can find the lecture notes and exercises for this lecture at https://missing.csail.mit.edu/2020/course-shell/
Help us caption & translate this video!
https://amara.org/v/C1Efe/
Help us caption & translate this video!
https://amara.org/v/C1Efe/
MediaPipe Hand
MediaPipe Hand is a high-fidelity hand and finger tracking solution. GitHub : https://github.com/google/mediapipe
#DeepLearning #MachineLearning #MediaPipe
MediaPipe Hand is a high-fidelity hand and finger tracking solution. GitHub : https://github.com/google/mediapipe
#DeepLearning #MachineLearning #MediaPipe
GitHub
GitHub - google-ai-edge/mediapipe: Cross-platform, customizable ML solutions for live and streaming media.
Cross-platform, customizable ML solutions for live and streaming media. - google-ai-edge/mediapipe
End-to-End Object Detection with Transformers
Carion et al.: https://arxiv.org/abs/2005.12872
Colab: https://colab.research.google.com/drive/1rPm0-UrWHpJJRX9PsNb5SpzZiUlMh7wm
#ArtificialIntelligence #DeepLearning #Transformers
Carion et al.: https://arxiv.org/abs/2005.12872
Colab: https://colab.research.google.com/drive/1rPm0-UrWHpJJRX9PsNb5SpzZiUlMh7wm
#ArtificialIntelligence #DeepLearning #Transformers
Google
detr_demo.ipynb
Colaboratory notebook
Neuroevolution of Self-Interpretable Agents
Tang et al.: https://arxiv.org/abs/2003.08165
#NeuralComputing #EvolutionaryComputing #MachineLearning
Tang et al.: https://arxiv.org/abs/2003.08165
#NeuralComputing #EvolutionaryComputing #MachineLearning
Playing Atari with Six Neurons
Cuccu et al.: https://arxiv.org/abs/1806.01363
#MachineLearning #ArtificialIntelligence #NeuralComputing
Cuccu et al.: https://arxiv.org/abs/1806.01363
#MachineLearning #ArtificialIntelligence #NeuralComputing
arXiv.org
Playing Atari with Six Neurons
Deep reinforcement learning, applied to vision-based problems like Atari games, maps pixels directly to actions; internally, the deep neural network bears the responsibility of both extracting...
Improving the Neural Algorithm of Artistic Style
Roman Novak, Yaroslav Nikulin : https://arxiv.org/abs/1605.04603
#Art #DeepLearning #NeuralNetworks
Roman Novak, Yaroslav Nikulin : https://arxiv.org/abs/1605.04603
#Art #DeepLearning #NeuralNetworks
Stanford's Natural Language Processing with Deep Learning is one of the most respected courses on the topic that you will find anywhere, and the course materials are freely available online.
To be clear, this isn't a recent occurrence; Stanford's Natural Language Processing with Deep Learning (CS224n) materials have been available online for quite some time, years in fact, and the available materials are constantly being updated to closely reflect what the in-school course looks like at any given time. And to be even more clear, there is no option to enroll, as this is not a MOOC; it is simply the freely available materials from this world-class course on the topic of deep learning with NLP.
https://www.kdnuggets.com/2020/05/best-nlp-deep-learning-course-free.html
To be clear, this isn't a recent occurrence; Stanford's Natural Language Processing with Deep Learning (CS224n) materials have been available online for quite some time, years in fact, and the available materials are constantly being updated to closely reflect what the in-school course looks like at any given time. And to be even more clear, there is no option to enroll, as this is not a MOOC; it is simply the freely available materials from this world-class course on the topic of deep learning with NLP.
https://www.kdnuggets.com/2020/05/best-nlp-deep-learning-course-free.html
KDnuggets
The Best NLP with Deep Learning Course is Free - KDnuggets
Stanford's Natural Language Processing with Deep Learning is one of the most respected courses on the topic that you will find anywhere, and the course materials are freely available online.
List of Open-Source RL Algorithms
By Sergey Kolesnikov, https://docs.google.com/spreadsheets/d/1EeFPd-XIQ3mq_9snTlAZSsFY7Hbnmd7P5bbT8LPuMn0/edit#gid=0
#DeepLearning #MachineLearning #ReinforcementLearning
By Sergey Kolesnikov, https://docs.google.com/spreadsheets/d/1EeFPd-XIQ3mq_9snTlAZSsFY7Hbnmd7P5bbT8LPuMn0/edit#gid=0
#DeepLearning #MachineLearning #ReinforcementLearning
Google Docs
Open-source RL
There are hundreds of free research talks happening online these days.
This site organizes them by date, topic, institution and other categories.
Check out the 100+ offerings in CS: https://researchseminars.org/talks
(v/professors at MitMath) #onlinetalks #seminars #wednesdaywisdom
This site organizes them by date, topic, institution and other categories.
Check out the 100+ offerings in CS: https://researchseminars.org/talks
(v/professors at MitMath) #onlinetalks #seminars #wednesdaywisdom
researchseminars.org
researchseminars.org - Browse talks
Welcome to researchseminars.org, a list of research seminars and conferences!
@ArtificialIntelligenceArticles
https://spectrum.ieee.org/tech-talk/artificial-intelligence/machine-learning/yoshua-bengio-revered-architect-of-ai-has-some-ideas-about-what-to-build-next
@ArtificialIntelligenceArticles
https://spectrum.ieee.org/tech-talk/artificial-intelligence/machine-learning/yoshua-bengio-revered-architect-of-ai-has-some-ideas-about-what-to-build-next
@ArtificialIntelligenceArticles
IEEE Spectrum
Yoshua Bengio, Revered Architect of AI, Has Some Ideas About What to Build Next
The Turing Award winner wants AI systems that can reason, plan, and imagine
uergen Schmidhuber: Critique of Turing Award for Drs. Bengio & Hinton & LeCun
@ArtificialIntelligenceArticles
http://people.idsia.ch/~juergen/critique-turing-award-bengio-hinton-lecun.html
@ArtificialIntelligenceArticles
@ArtificialIntelligenceArticles
http://people.idsia.ch/~juergen/critique-turing-award-bengio-hinton-lecun.html
@ArtificialIntelligenceArticles
people.idsia.ch
Critique of Turing Award for Drs. Bengio & Hinton & LeCun
ACM lauds them for work that did not cite the origins of the used methods. But science is self-correcting (Nature 577 p 9, 2020).
AI Paper Summary Video
Paper: BERT: Pre-training of Deep Bidirectional Transformers forLanguage Understanding
Link: https://arxiv.org/pdf/1810.04805.pdf
Video Summary: https://youtu.be/M4rq1Ce6wyM
Summary by Dhruvil Karani (Data Scientist)
B.Eng. (IIT Guwahati)
Paper: BERT: Pre-training of Deep Bidirectional Transformers forLanguage Understanding
Link: https://arxiv.org/pdf/1810.04805.pdf
Video Summary: https://youtu.be/M4rq1Ce6wyM
Summary by Dhruvil Karani (Data Scientist)
B.Eng. (IIT Guwahati)
YouTube
BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding (AI Paper Summary)
Paper: BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding
Link: https://arxiv.org/pdf/1810.04805.pdf
Summary by Dhruvil Karani (Data Scientist)
B.Eng. (IIT Guwahati)
Link: https://arxiv.org/pdf/1810.04805.pdf
Summary by Dhruvil Karani (Data Scientist)
B.Eng. (IIT Guwahati)