Ecosyste.ms: Awesome
An open API service indexing awesome lists of open source software.
-awesome-artificial-intelligence
A curated list of Artificial Intelligence (AI) courses, books, video lectures and papers
https://github.com/eric-erki/-awesome-artificial-intelligence
Last synced: 1 day ago
JSON representation
-
Courses
- Deep Blueberry: Deep Learning book - A free five-weekend plan to self-learners to learn the basics of deep-learning architectures like CNNs, LSTMs, RNNs, VAEs, GANs, DQN, A3C and more
- MIT Artifical Intelligence Videos - MIT AI Course
- Grokking Deep Learning in Motion - Beginner's course to learn deep learning and neural networks without frameworks.
- Intro to Artificial Intelligence - Learn the Fundamentals of AI. Course run by Peter Norvig
- Machine Learning - Basic machine learning algorithms for supervised and unsupervised learning
- Deep Learning - An Introductory course to the world of Deep Learning.
- Stanford Statistical Learning - Introductory course on machine learning focusing on: linear and polynomial regression, logistic regression and linear discriminant analysis; cross-validation and the bootstrap, model selection and regularization methods (ridge and lasso); nonlinear models, splines and generalized additive models; tree-based methods, random forests and boosting; support-vector machines.
- Deep RL Bootcamp Lectures - Deep Reinforcement Bootcamp Lectures - August 2017
- Deep Learning Crash Course
- list of recommended reading
- Reinforcement Learning: An Introduction - This introductory textbook on reinforcement learning is targeted toward engineers and scientists in artificial intelligence, operations research, neural networks, and control systems, and we hope it will also be of interest to psychologists and neuroscientists.
- Deep Learning with PyTorch - PyTorch puts these superpowers in your hands, providing a comfortable Python experience that gets you started quickly and then grows with you as you—and your deep learning skills—become more sophisticated. Deep Learning with PyTorch will make that journey engaging and fun.
- Deep Reinforcement Learning in Action - Deep Reinforcement Learning in Action teaches you the fundamental concepts and terminology of deep reinforcement learning, along with the practical skills and techniques you’ll need to implement it into your own projects.
- Elements of AI (Part 1) - Reaktor/University of Helsinki - An Introduction to AI is a free online course for everyone interested in learning what AI is, what is possible (and not possible) with AI, and how it affects our lives – with no complicated math or programming required.
- Deep Learning and the Game of Go - Deep Learning and the Game of Go teaches you how to apply the power of deep learning to complex human-flavored reasoning tasks by building a Go-playing AI. After exposing you to the foundations of machine and deep learning, you'll use Python to build a bot and then teach it the rules of the game.
- Deep Learning for Search - Deep Learning for Search teaches you how to leverage neural networks, NLP, and deep learning techniques to improve search performance.
- Grokking Deep Reinforcement Learning - Grokking Deep Reinforcement Learning introduces this powerful machine learning approach, using examples, illustrations, exercises, and crystal-clear teaching.
- Fusion in Action - Fusion in Action teaches you to build a full-featured data analytics pipeline, including document and data search and distributed data clustering.
- Real-World Natural Language Processing - Early access book on how to create practical NLP applications using Python.
- Grokking Machine Learning - Early access book that introduces the most valuable machine learning techniques.
- Succeeding with AI - An introduction to managing successful AI projects and applying AI to real-life situations.
- Machine Learning Crash Course By Google - world case studies, and hands-on practice exercises.
- Knowledge Based Artificial Intelligence - Georgia Tech's course on Artificial Intelligence focussing on Symbolic AI.
- Neural Networks For Machine Learning - Algorithmic and practical tricks for artifical neural networks.
-
Philosophy
- Super Intelligence - Superintelligence asks the questions: What happens when machines surpass humans in general intelligence. A really great book.
- Life 3.0: Being Human in the Age of Artificial Intelligence - Max Tegmark, professor of Physics at MIT, discusses how Artificial Intelligence may affect crime, war, justice, jobs, society and our very sense of being human both in the near and far future.
- Super Intelligence - Superintelligence asks the questions: What happens when machines surpass humans in general intelligence. A really great book.
- Our Final Invention: Artificial Intelligence And The End Of The Human Era - Our Final Invention explores the perils of the heedless pursuit of advanced AI. Until now, human intelligence has had no rival. Can we coexist with beings whose intelligence dwarfs our own? And will they allow us to?
- How to Create a Mind: The Secret of Human Thought Revealed - Ray Kurzweil, director of engineering at Google, explored the process of reverse-engineering the brain to understand precisely how it works, then applies that knowledge to create vastly intelligent machines.
- Our Final Invention: Artificial Intelligence And The End Of The Human Era - Our Final Invention explores the perils of the heedless pursuit of advanced AI. Until now, human intelligence has had no rival. Can we coexist with beings whose intelligence dwarfs our own? And will they allow us to?
-
Programming
- Prolog Programming For Artificial Intelligence - This best-selling guide to Prolog and Artificial Intelligence concentrates on the art of using the basic mechanisms of Prolog to solve interesting AI problems.
- Python for Artificial Intelligence
- Python Tools for Machine Learning
-
Organizations
-
Free Content
- Foundations Of Computational Agents - This book is published by Cambridge University Press, 2010
- The Quest For Artificial Intelligence - This book traces the history of the subject, from the early dreams of eighteenth-century (and earlier) pioneers to the more successful work of today's AI engineers.
- Stanford CS229 - Machine Learning - This course provides a broad introduction to machine learning and statistical pattern recognition.
- Computers and Thought: A practical Introduction to Artificial Intelligence - The book covers computer simulation of human activities, such as problem solving and natural language understanding; computer vision; AI tools and techniques; an introduction to AI programming; symbolic and neural network models of cognition; the nature of mind and intelligence; and the social implications of AI and cognitive science.
- Society of Mind - Marvin Minsky's seminal work on how our mind works. Lot of Symbolic AI concepts have been derived from this basis.
- Artificial Intelligence and Molecular Biology - The current volume is an effort to bridge that range of exploration, from nucleotide to abstract concept, in contemporary AI/MB research.
- Brief Introduction To Educational Implications Of Artificial Intelligence - This book is designed to help preservice and inservice teachers learn about some of the educational implications of current uses of Artificial Intelligence as an aid to solving problems and accomplishing tasks.
- Encyclopedia: Computational intelligence - Scholarpedia is a peer-reviewed open-access encyclopedia written and maintained by scholarly experts from around the world.
- Ethical Artificial Intelligence - a book by Bill Hibbard that combines several peer reviewed papers and new material to analyze the issues of ethical artificial intelligence.
- Golden Artificial Intelligence - a cluster of pages on artificial intelligence and machine learning.
- R2D3 - A website with explanations on topics from Machine Learning to Statistics. All helped with beautiful animated infographics and real life examples. Available in various languages.
-
Learning
- Professional and In-Depth Deep Learning Video Courses - A collection of free professional and in depth Deep Learning video tutorials and courses
- Deep Learning. Methods And Applications
- Deep Learning - Yoshua Bengio, Ian Goodfellow and Aaron Courville put together this currently free (and draft version) book on deep learning. The book is kept up-to-date and covers a wide range of topics in depth (up to and including sequence-to-sequence learning).
- Deep Learning.net - Aggregation site for DL resources
- Awesome Machine Learning - Like this Github, but ML-focused
- FastML
- Awesome Deep Learning Resources - Rough list of learning resources for Deep Learning
- Professional and In-Depth Machine Learning Video Courses - A collection of free professional and in depth Machine Learning and Data Science video tutorials and courses
- Professional and In-Depth Artificial Intelligence Video Courses - A collection of free professional and in depth Artificial Intelligence video tutorials and courses
- Machine Learning Mastery
-
Books
- How Machine Learning Works - Mostafa Samir. Early access book that introduces machine learning from both practical and theoretical aspects in a non-threating way.
-
Code
-
Videos
- Intelligent agents and paradigms for AI
- The Unreasonable Effectiveness Of Deep Learning - The Director of Facebook's AI Research, Dr. Yann LeCun gives a talk on deep convolutional neural networks and their applications to machine learning and computer vision
- AWS Machine Learning in Motion - This interactive liveVideo course gives you a crash course in using AWS for machine learning, teaching you how to build a fully-working predictive algorithm.
- Deep Learning with R in Motion - Deep Learning with R in Motion teaches you to apply deep learning to text and images using the powerful Keras library and its R language interface.
- Reinforcement Learning in Motion - This liveVideo breaks down key concepts like how RL systems learn, how to sense and process environmental data, and how to build and train AI agents.
- Grokking Deep Learning in Motion - Grokking Deep Learning in Motion will not just teach you how to use a single library or framework, you’ll actually discover how to build these algorithms completely from scratch!
-
Journals
- AI & Society
- Annals of Mathematics and Artifical Intelligence
- Applicable Algebra in Engineering, Communication and Computing
- Applied Artificial Intelligence
- Applied Intelligence
- Artificial Intelligence Review
- Automated Software Engineering
- Autonomous Agents and Multi-Agent Systems
- Computational and Mathematical Organization Theory
- Computational Intelligence
- Electronic Transactions on Artificial Intelligence
- Evolutionary Intelligence
- Intelligent Industrial Systems
- International Journal of Intelligent Systems
- International Journal on Artificial Intelligence Tools
- Journal of Automated Reasoning
- Journal of Intelligent Information Systems
- Journal on Data Semantics
- Minds and Machines
- Progress in Artificial Intelligence
- EXPERT—IEEE Intelligent Systems
-
Competitions
-
Newsletters
-
Misc
- AIResources - Directory of open source software and open access data for the AI research community
- Artificial Intelligence Subreddit
Programming Languages
Categories
Sub Categories
Keywords
deep-learning
2
machine-learning
2
computer-vision
1
convolutional-neural-networks
1
deep-learning-algorithms
1
deep-learning-tutorial
1
deep-neural-networks
1
deep-reinforcement-learning
1
generative-adversarial-network
1
keras-tensorflow
1
long-short-term-memory
1
machine-learning-algorithms
1
pytorch-implementation
1
pytorch-tutorial
1
recurrent-neural-networks
1
reinforcement-learning
1
variational-autoencoder
1
awesome
1
awesome-list
1
cnn
1
lstm
1
tensorflow
1