François Chollet is the creator of Keras, which is an open source deep learning library that is designed to enable fast, user-friendly experimentation with deep neural networks. It serves as an interface to several deep learning libraries, most popular of which is TensorFlow, and it was integrated into TensorFlow main codebase a while back. Aside from creating an exceptionally useful and popular library, François is also a world-class AI researcher and software engineer at Google, and is definitely an outspoken, if not controversial, personality in the AI world, especially in the realm of ideas around the future of artificial intelligence. This conversation is part of the Artificial Intelligence podcast.
https://www.youtube.com/watch?v=Bo8MY4JpiXE&t=173s
#machine_learning #artificial_intelligence #podcast
https://www.youtube.com/watch?v=Bo8MY4JpiXE&t=173s
#machine_learning #artificial_intelligence #podcast
YouTube
François Chollet: Keras, Deep Learning, and the Progress of AI | Artificial Intelligence Podcast
François Chollet is the creator of Keras, which is an open source deep learning library that is designed to enable fast, user-friendly experimentation with d...
A great and comprehensive review of meta-learning algorithms
https://lilianweng.github.io/lil-log/2018/11/30/meta-learning.html
#meta_learning #deep_learning #machine_learning
https://lilianweng.github.io/lil-log/2018/11/30/meta-learning.html
#meta_learning #deep_learning #machine_learning
Lil'Log
Meta Learning
The purpose of this handout is to help you use statistics to make your argument as effectively as possible, especially in your research paper.
https://writingcenter.unc.edu/tips-and-tools/statistics/
https://writingcenter.unc.edu/tips-and-tools/statistics/
The Writing Center • University of North Carolina at Chapel Hill
Statistics – The Writing Center • University of North Carolina at Chapel Hill
There are lies, damned lies, and statistics. —Mark Twain What this handout is about The purpose of this handout is to help you use statistics to make your argument as effectively as possible. Introduction Numbers are power. Apparently freed of … Read more
Genetic Neural Architecture Search.pdf
1.5 MB
Today I published the pre-print version of my first paper which is about designing a new evolutionary algorithm for neural architecture search in Arxiv.
https://arxiv.org/abs/1909.09432
https://arxiv.org/abs/1909.09432
A set of tutorials and courses on Geometric Deep Learning:
https://people.lu.usi.ch/bronstem/teaching_tutorial.html
#deep_learning #geometric_deep_learning #machine_learning
https://people.lu.usi.ch/bronstem/teaching_tutorial.html
#deep_learning #geometric_deep_learning #machine_learning
A curated list of resources dedicated to Natural Language Processing (NLP)
https://github.com/keon/awesome-nlp
#nlp #deep_learning
https://github.com/keon/awesome-nlp
#nlp #deep_learning
GitHub
GitHub - keon/awesome-nlp: :book: A curated list of resources dedicated to Natural Language Processing (NLP)
:book: A curated list of resources dedicated to Natural Language Processing (NLP) - keon/awesome-nlp
A fascinating Youtube Channel for learning various mathematical concepts:
https://www.youtube.com/channel/UCFe6jenM1Bc54qtBsIJGRZQ
#mathematics
https://www.youtube.com/channel/UCFe6jenM1Bc54qtBsIJGRZQ
#mathematics
YouTube
Patrick J
Howdy!
I've been creating free Mathematics videos since 2007 and continue to do so.
Teachers please feel free to reach out if I can help you although I do get a lot of emails! You can find my email below next to the 'For Business Inquiries' box!
If you…
I've been creating free Mathematics videos since 2007 and continue to do so.
Teachers please feel free to reach out if I can help you although I do get a lot of emails! You can find my email below next to the 'For Business Inquiries' box!
If you…
Lectures Slides of Signal Processing for Machine Learning Course by Stanfrod University
https://web.stanford.edu/class/ee269/slides.html
#mathematics #machine_learning
https://web.stanford.edu/class/ee269/slides.html
#mathematics #machine_learning
A great course about Digital Signal Processing, presented by EPFL
https://www.coursera.org/learn/dsp
#mathematics #electrical_engineering
https://www.coursera.org/learn/dsp
#mathematics #electrical_engineering
Coursera
Digital Signal Processing 1: Basic Concepts and Algorithms
Offered by École Polytechnique Fédérale de Lausanne. ... Enroll for free.
Good tips for multiprocessing in Python:
https://www.cloudcity.io/blog/2019/02/27/things-i-wish-they-told-me-about-multiprocessing-in-python/
#python #parallel_programming
https://www.cloudcity.io/blog/2019/02/27/things-i-wish-they-told-me-about-multiprocessing-in-python/
#python #parallel_programming
Cloud City Development
Things I Wish They Told Me About Multiprocessing in Python
Framing the problem
“Some people, when confronted with a problem, think ‘I know, I’ll use multithreading’. Nothhw tpe yawrve o oblems.” (Eiríkr Åsheim, 2012)
If multithreading is so problematic, though, how do we take advantage of systems with 8, 16, 32…
“Some people, when confronted with a problem, think ‘I know, I’ll use multithreading’. Nothhw tpe yawrve o oblems.” (Eiríkr Åsheim, 2012)
If multithreading is so problematic, though, how do we take advantage of systems with 8, 16, 32…
The Math of Machine Learning - Berkeley University Textbook
The mathematical skills you need for starting your journey into the field of Machine Learning
Note: It should be noted that It doesn't cover all the mathematical skills you need for doing ML during your life, It's just a brief textbook which could help you to start learning more complicated mathematical concepts in ML
https://www.datasciencecentral.com/profiles/blogs/tutorial-the-math-of-machine-learning-berkeley-university
#mahine_learning #mathematics
The mathematical skills you need for starting your journey into the field of Machine Learning
Note: It should be noted that It doesn't cover all the mathematical skills you need for doing ML during your life, It's just a brief textbook which could help you to start learning more complicated mathematical concepts in ML
https://www.datasciencecentral.com/profiles/blogs/tutorial-the-math-of-machine-learning-berkeley-university
#mahine_learning #mathematics
Data Science Central
The Math of Machine Learning - Berkeley University Textbook - DataScienceCentral.com
This document is an attempt to provide a summary of the mathematical background needed for an introductory class in machine learning, which at UC Berkeley is known as CS 189/289A. Our assumption is that the reader is already familiar with the basic concepts…
Pytest Library
The pytest framework makes it easy to write small tests, yet scales to support complex functional testing for applications and libraries.
https://doc.pytest.org/en/latest/#
#python #programming
The pytest framework makes it easy to write small tests, yet scales to support complex functional testing for applications and libraries.
https://doc.pytest.org/en/latest/#
#python #programming
Solving Rubik’s Cube with a Robot Hand
This is fascinating, make sure you read it.
Summary: OpenAI team trained a pair of neural networks to solve the Rubik’s Cube with a human-like robot hand. The neural networks are trained entirely in simulation, using the same reinforcement learning code as OpenAI Five paired with a new technique called Automatic Domain Randomization (ADR). The system can handle situations it never saw during training, such as being prodded by a stuffed giraffe. This shows that reinforcement learning isn’t just a tool for virtual tasks, but can solve physical-world problems requiring unprecedented dexterity.
https://openai.com/blog/solving-rubiks-cube/
#reinforcement_learning #machine_learning #robotics
This is fascinating, make sure you read it.
Summary: OpenAI team trained a pair of neural networks to solve the Rubik’s Cube with a human-like robot hand. The neural networks are trained entirely in simulation, using the same reinforcement learning code as OpenAI Five paired with a new technique called Automatic Domain Randomization (ADR). The system can handle situations it never saw during training, such as being prodded by a stuffed giraffe. This shows that reinforcement learning isn’t just a tool for virtual tasks, but can solve physical-world problems requiring unprecedented dexterity.
https://openai.com/blog/solving-rubiks-cube/
#reinforcement_learning #machine_learning #robotics
Openai
Solving Rubik’s Cube with a robot hand
We’ve trained a pair of neural networks to solve the Rubik’s Cube with a human-like robot hand. The neural networks are trained entirely in simulation, using the same reinforcement learning code as OpenAI Five paired with a new technique called Automatic…
Proximal Policy Optimization
Paper:
https://openai.com/blog/openai-baselines-ppo/
YouTube Video:
https://www.youtube.com/watch?v=5P7I-xPq8u8&list=PLLO4N3-FoY3feUsA3_XZvn5sXy9Ms8ayE&index=2
#reinforcement_learning #optimization
Paper:
https://openai.com/blog/openai-baselines-ppo/
YouTube Video:
https://www.youtube.com/watch?v=5P7I-xPq8u8&list=PLLO4N3-FoY3feUsA3_XZvn5sXy9Ms8ayE&index=2
#reinforcement_learning #optimization
Openai
Proximal Policy Optimization
We’re releasing a new class of reinforcement learning algorithms, Proximal Policy Optimization (PPO), which perform comparably or better than state-of-the-art approaches while being much simpler to implement and tune. PPO has become the default reinforcement…
PyTorch tutorial of various RL algorithms:
actor critic / proximal policy optimization / acer / ddpg / twin dueling ddpg / soft actor critic / generative adversarial imitation learning / hindsight experience replay
https://github.com/higgsfield/RL-Adventure-2
#reinforcement_learning #pytorch
actor critic / proximal policy optimization / acer / ddpg / twin dueling ddpg / soft actor critic / generative adversarial imitation learning / hindsight experience replay
https://github.com/higgsfield/RL-Adventure-2
#reinforcement_learning #pytorch
GitHub
GitHub - higgsfield-ai/higgsfield: Fault-tolerant, highly scalable GPU orchestration, and a machine learning framework designed…
Fault-tolerant, highly scalable GPU orchestration, and a machine learning framework designed for training models with billions to trillions of parameters - higgsfield-ai/higgsfield
Forwarded from Machine Learning World
Michio Kaku: Future of Humans, Aliens, Space Travel & Physics | Artificial Intelligence (AI) Podcast
Michio Kaku is a theoretical physicist, futurist, and professor at the City College of New York. He is the author of many fascinating books on the nature of our reality and the future of our civilization. This conversation is part of the Artificial Intelligence podcast.
https://www.youtube.com/watch?v=kD5yc1LQrpQ
#artificial_intelligence #physics #cosmology
Michio Kaku is a theoretical physicist, futurist, and professor at the City College of New York. He is the author of many fascinating books on the nature of our reality and the future of our civilization. This conversation is part of the Artificial Intelligence podcast.
https://www.youtube.com/watch?v=kD5yc1LQrpQ
#artificial_intelligence #physics #cosmology
YouTube
Michio Kaku: Future of Humans, Aliens, Space Travel & Physics | Lex Fridman Podcast #45