awesome-awesomeness/html/artificialintelligence.md2.html

<h1 id="awesome-artificial-intelligence-ai-awesome">Awesome Artificial
Intelligence (AI) <a href="https://github.com/sindresorhus/awesome"><img
src="https://cdn.rawgit.com/sindresorhus/awesome/d7305f38d29fed78fa85652e3a63e154dd8e8829/media/badge.svg"
alt="Awesome" /></a></h1>
<p>This is a curated list of Artificial Intelligence (AI) tools,
courses, books, lectures, and papers. AI, or Artificial Intelligence, is
a branch of computer science focused on creating machines that can
perform tasks requiring human-like intelligence. These tasks include
learning, reasoning, problem-solving, understanding natural language,
and recognizing patterns. AI aims to mimic human cognitive functions,
making machines capable of improving their performance based on
experience, adapting to new inputs, and performing human-like tasks.</p>
<p>Contributions are welcome. Connect on <a
href="https://www.linkedin.com/in/owainlewis82/">LinkedIn</a> or <a
href="https://twitter.com/owainlewis">X</a>.</p>
<p><img
src="https://media.giphy.com/media/jeAQYN9FfROX6/giphy.gif" /></p>
<h2 id="contents">Contents</h2>
<ol type="1">
<li><a href="#tools">Tools</a></li>
<li><a href="#courses">Courses</a></li>
<li><a href="#books">Books</a></li>
<li><a href="#programming">Programming</a></li>
<li><a href="#philosophy">Philosophy</a></li>
<li><a href="#free-content">Free Content</a></li>
<li><a href="#code">Code</a></li>
<li><a href="#videos">Videos</a></li>
<li><a href="#learning">Learning</a></li>
<li><a href="#organizations">Organizations</a></li>
<li><a href="#journals">Journals</a></li>
<li><a href="#competitions">Competitions</a></li>
<li><a href="#newsletters">Newsletters</a></li>
<li><a href="#misc">Misc</a></li>
</ol>
<h2 id="tools">Tools</h2>
<h3 id="chat">Chat</h3>
<ul>
<li><a href="https://chat.openai.com/">Chat GPT</a> ChatGPT is a
free-to-use AI system. It allows users to engage in conversations, gain
insights, automate tasks, and witness the future of AI all in one
place.</li>
<li><a href="https://gemini.google.com/">Gemini</a> Gemini gives you
direct access to Google AI. Get help with writing, planning, learning,
and more.</li>
<li><a href="https://www.anthropic.com/claude">Claude</a> Claude is a
family of foundational AI models that can be used in various
applications. You can talk directly with Claude at claude.ai to
brainstorm ideas, analyze images, and process long documents</li>
</ul>
<h3 id="images">Images</h3>
<ul>
<li><a href="https://www.midjourney.com/">Midjourney</a> AI image
generation</li>
<li><a href="https://openai.com/dall-e-3">DALL·E 2</a> DALL·E 3 is an AI
system that can create realistic images and art from a natural-language
description.</li>
</ul>
<h3 id="video">Video</h3>
<ul>
<li><a href="https://openai.com/sora">Sora</a> Sora is a text-to-video
AI model that can create realistic and imaginative scenes from text
instructions.</li>
<li><a href="https://runwayml.com/">Runway</a> AI video generation</li>
</ul>
<h3 id="commerical-tools">Commerical Tools</h3>
<ul>
<li><a href="https://www.taskade.com">Taskade</a> Build, train, and
deploy AI agents to automate tasks, research, and collaborate in
real-time</li>
</ul>
<h2 id="courses">Courses</h2>
<ul>
<li><a
href="https://www.notion.so/owainlewis/Introduction-to-Artificial-Intelligence-AI-ef59b363654542e597ba46a19d129882?pvs=4">Introduction
to Artificial Intelligence (AI)</a> - A high-level introduction to AI
from IBM on Coursera</li>
<li><a
href="https://www.coursera.org/learn/introduction-to-generative-ai">Introduction
to Generative AI</a> - A beginner-level introduction to Generative AI
from Google on Coursera</li>
<li><a href="https://cs50.harvard.edu/ai/2020">CS50’s Intro to
Artificial Intelligence</a> - This course explores the concepts and
algorithms at the foundation of modern artificial intelligence</li>
<li><a href="https://introtodeeplearning.com">MIT: Intro to Deep
Learning</a> - A seven-day bootcamp designed in MIT to introduce deep
learning methods and applications</li>
<li><a href="https://mithi.github.io/deep-blueberry">Deep Blueberry:
Deep Learning book</a> - A free five-weekend plan for self-learners to
learn the basics of deep-learning architectures like CNNs, LSTMs, RNNs,
VAEs, GANs, DQN, A3C and more</li>
<li><a href="https://spinningup.openai.com/">Spinning Up in Deep
Reinforcement Learning</a> - A free deep reinforcement learning course
by OpenAI</li>
<li><a
href="http://ocw.mit.edu/courses/electrical-engineering-and-computer-science/6-034-artificial-intelligence-fall-2010/lecture-videos">MIT
Artificial Intelligence Videos</a> - MIT AI Course</li>
<li><a
href="https://www.manning.com/livevideo/grokking-deep-learning-in-motion?a_aid=algmotion&amp;a_bid=5d7bc0ba">Grokking
Deep Learning in Motion</a> - Beginner’s course to learn deep learning
and neural networks without frameworks.</li>
<li><a href="https://www.udacity.com/course/cs271">Intro to Artificial
Intelligence</a> - Learn the Fundamentals of AI. Course run by Peter
Norvig</li>
<li><a
href="https://www.edx.org/course/artificial-intelligence-uc-berkeleyx-cs188-1x-0#.VMeIsmSsVkg">EdX
Artificial Intelligence</a> - The course will introduce the basic ideas
and techniques underlying the design of intelligent computer
systems</li>
<li><a
href="https://www.class-central.com/mooc/319/udacity-artificial-intelligence-for-robotics">Artificial
Intelligence For Robotics</a> - This class will teach you basic methods
in Artificial Intelligence, including probabilistic inference, planning
and search, localization, tracking and control, all with a focus on
robotics</li>
<li><a href="https://class.coursera.org/ml-008">Machine Learning</a> -
Basic machine learning algorithms for supervised and unsupervised
learning</li>
<li><a
href="https://www.udacity.com/course/intro-to-tensorflow-for-deep-learning--ud187">Deep
Learning</a> - An Introductory course to Deep Learning using
TensorFlow.</li>
<li><a
href="http://online.stanford.edu/course/statistical-learning-winter-2014">Stanford
Statistical Learning</a> - 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.</li>
<li><a
href="https://www.udacity.com/course/knowledge-based-ai-cognitive-systems--ud409">Knowledge
Based Artificial Intelligence</a> - Georgia Tech’s course on Artificial
Intelligence focussing on Symbolic AI.</li>
<li><a
href="https://sites.google.com/view/deep-rl-bootcamp/lectures">Deep RL
Bootcamp Lectures</a> - Deep Reinforcement Bootcamp Lectures - August
2017</li>
<li><a
href="https://developers.google.com/machine-learning/crash-course/ml-intro">Machine
Learning Crash Course By Google</a> Machine Learning Crash Course
features a series of lessons with video lectures, real-world case
studies, and hands-on practice exercises.</li>
<li><a href="https://developers.google.com/edu/python/">Python Class By
Google</a> This is a free class for people with a little bit of
programming experience who want to learn Python. The class includes
written materials, lecture videos, and lots of code exercises to
practice Python coding.</li>
<li><a
href="https://www.manning.com/livevideo/deep-learning-crash-course">Deep
Learning Crash Course</a> In this liveVideo course, machine learning
expert Oliver Zeigermann teaches you the basics of deep learning.</li>
<li><a
href="http://www.amazon.com/Artificial-Intelligence-Modern-Approach-3rd/dp/0136042597">Artificial
Intelligence: A Modern Approach</a> - Stuart Russell &amp; Peter Norvig
<ul>
<li>Also consider browsing the <a
href="http://aima.cs.berkeley.edu/books.html">list of recommended
reading</a>, divided by each chapter in “Artificial Intelligence: A
Modern Approach”.</li>
</ul></li>
<li><a
href="http://www.amazon.com/exec/obidos/ASIN/1558601910">Paradigms Of
Artificial Intelligence Programming: Case Studies in Common Lisp</a> -
Paradigms of AI Programming is the first text to teach advanced Common
Lisp techniques in the context of building major AI systems</li>
<li><a
href="http://www.freetechbooks.com/reinforcement-learning-an-introduction-second-edition-draft-t1282.html">Reinforcement
Learning: An Introduction</a> - 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.</li>
<li><a
href="http://www.amazon.com/Cambridge-Handbook-Artificial-Intelligence/dp/0521691915">The
Cambridge Handbook Of Artificial Intelligence</a> - Written for
non-specialists, it covers the discipline’s foundations, major theories,
and principal research areas, plus related topics such as artificial
life</li>
<li><a href="http://www.amazon.com/gp/product/0743276647">The Emotion
Machine: Commonsense Thinking, Artificial Intelligence, and the Future
of the Human Mind</a> - In this mind-expanding book, scientific pioneer
Marvin Minsky continues his groundbreaking research, offering a
fascinating new model for how our minds work</li>
<li><a
href="http://www.amazon.com/Artificial-Intelligence-Synthesis-Nils-Nilsson/dp/1558604677">Artificial
Intelligence: A New Synthesis</a> - Beginning with elementary reactive
agents, Nilsson gradually increases their cognitive horsepower to
illustrate the most important and lasting ideas in AI</li>
<li><a
href="http://www.amazon.com/Jeff-Hawkins/e/B001KHNZ7C/ref=sr_ntt_srch_lnk_11?qid=1435480927&amp;sr=8-11">On
Intelligence</a> - Hawkins develops a powerful theory of how the human
brain works, explaining why computers are not intelligent and how, based
on this new theory, we can finally build intelligent machines. Also
audio version available from audible.com</li>
<li><a
href="http://www.amazon.com/How-Create-Mind-Thought-Revealed/dp/0143124048/ref=pd_sim_14_3?ie=UTF8&amp;refRID=0QY72H7NGRYH79R7S3K7">How
To Create A Mind</a> - Kurzweil discusses how the brain works, how the
mind emerges, brain-computer interfaces, and the implications of vastly
increasing the powers of our intelligence to address the world’s
problems</li>
<li><a href="http://www.deeplearningbook.org/">Deep Learning</a> -
Goodfellow, Bengio and Courville’s introduction to a broad range of
topics in deep learning, covering mathematical and conceptual
background, deep learning techniques used in industry, and research
perspectives.</li>
<li><a href="https://web.stanford.edu/~hastie/ElemStatLearn/">The
Elements of Statistical Learning: Data Mining, Inference, and
Prediction</a> - Hastie and Tibshirani cover a broad range of topics,
from supervised learning (prediction) to unsupervised learning including
neural networks, support vector machines, classification trees and
boosting—the first comprehensive treatment of this topic in any
book.</li>
<li><a
href="https://www.manning.com/books/deep-learning-and-the-game-of-go">Deep
Learning and the Game of Go</a> - 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.</li>
<li><a
href="https://www.manning.com/books/deep-learning-for-search">Deep
Learning for Search</a> - Deep Learning for Search teaches you how to
leverage neural networks, NLP, and deep learning techniques to improve
search performance.</li>
<li><a
href="https://www.manning.com/books/deep-learning-with-pytorch">Deep
Learning with PyTorch</a> - 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.</li>
<li><a
href="https://www.manning.com/books/deep-reinforcement-learning-in-action">Deep
Reinforcement Learning in Action</a> - 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.</li>
<li><a
href="https://www.manning.com/books/grokking-deep-reinforcement-learning">Grokking
Deep Reinforcement Learning</a> - Grokking Deep Reinforcement Learning
introduces this powerful machine learning approach, using examples,
illustrations, exercises, and crystal-clear teaching.</li>
<li><a href="https://www.manning.com/books/fusion-in-action">Fusion in
Action</a> - Fusion in Action teaches you to build a full-featured data
analytics pipeline, including document and data search and distributed
data clustering.</li>
<li><a
href="https://www.manning.com/books/real-world-natural-language-processing">Real-World
Natural Language Processing</a> - Early access book on how to create
practical NLP applications using Python.</li>
<li><a
href="https://www.manning.com/books/grokking-machine-learning">Grokking
Machine Learning</a> - Early access book that introduces the most
valuable machine learning techniques.</li>
<li><a
href="https://www.manning.com/books/succeeding-with-ai">Succeeding with
AI</a> - An introduction to managing successful AI projects and applying
AI to real-life situations.</li>
<li><a href="https://www.elementsofai.com/">Elements of AI (Part 1) -
Reaktor/University of Helsinki</a> - 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.</li>
<li><a
href="https://www.manning.com/books/essential-natural-language-processing">Essential
Natural Language Processing</a> - A hands-on guide to NLP with practical
techniques, numerous Python-based examples and real-world case
studies.</li>
<li><a href="https://www.kaggle.com/learn/overview">Kaggle’s micro
courses</a> - A series of micro courses by offering practical and
hands-on knowledge ranging from Python to Deep Learning.</li>
<li><a
href="https://www.manning.com/books/transfer-learning-for-natural-language-processing?utm_source=github&amp;utm_medium=organic&amp;utm_campaign=book_azunre_transfer_3_10_20">Transfer
Learning for Natural Language Processing</a> - A book that gets you up
to speed with the relevant ML concepts and then dives into transfer
learning for NLP.</li>
<li>(Stanford Deep Learning
Series][https://www.youtube.com/playlist?list=PLoROMvodv4rOABXSygHTsbvUz4G_YQhOb]</li>
<li><a
href="https://docs.aws.amazon.com/machine-learning/latest/dg/machinelearning-dg.pdf">Amazon
Machine Learning Developer Guide</a> - A book for ML developers which
introduces the ML concepts &amp; strategies with lots of practical
usages.</li>
<li><a href="https://arize.com/blog-course/">Machine Learning
Observability Course</a> - Self-guided course covers the intuition,
math, and best practices for effective machine learning
observability.</li>
<li><a
href="https://medium.com/machine-learning-for-humans/why-machine-learning-matters-6164faf1df12">Machine
Learning for Humans</a> - A series of simple, plain-English explanations
accompanied by math, code, and real-world examples.</li>
</ul>
<h2 id="books">Books</h2>
<ul>
<li><a
href="https://www.manning.com/books/machine-learning-for-mortals-mere-and-otherwise">Machine
Learning for Mortals (Mere and Otherwise)</a> - Early access book that
provides basics of machine learning and using R programming
language.</li>
<li><a
href="https://livebook.manning.com/book/how-machine-learning-works/welcome/v-5">How
Machine Learning Works</a> - Mostafa Samir. Early access book that
introduces machine learning from both practical and theoretical aspects
in a non-threatening way.</li>
<li><a
href="https://www.manning.com/books/machine-learning-with-tensorflow-second-edition">MachineLearningWithTensorFlow2ed</a>
is a book on general-purpose machine learning techniques, including
regression, classification, unsupervised clustering, reinforcement
learning, autoencoders, convolutional neural networks, RNNs, and LSTMs,
using TensorFlow 1.14.1.</li>
<li><a
href="https://www.manning.com/books/serverless-machine-learning-in-action">Serverless
Machine Learning</a> - a book for machine learning engineers on how to
train and deploy machine learning systems on public clouds like AWS,
Azure, and GCP, using a code-oriented approach.</li>
<li><a href="http://themlbook.com/">The Hundred-Page Machine Learning
Book</a> - all you need to know about Machine Learning in a hundred
pages, supervised and unsupervised learning, SVM, neural networks,
ensemble methods, gradient descent, cluster analysis and dimensionality
reduction, autoencoders and transfer learning, feature engineering and
hyperparameter tuning.</li>
<li><a
href="https://www.manning.com/books/trust-in-machine-learning">Trust in
Machine Learning</a> - a book for experienced data scientists and
machine learning engineers on how to make your AI a trustworthy partner.
Build machine learning systems that are explainable, robust,
transparent, and optimized for fairness.</li>
<li><a
href="https://www.manning.com/books/generative-ai-in-action">Generative
AI in Action</a> - A book that shows exactly how to add generative AI
tools for text, images, and code, and more into your organization’s
strategies and projects..</li>
</ul>
<h2 id="programming">Programming</h2>
<ul>
<li><a
href="http://www.amazon.com/Programming-Artificial-Intelligence-International-Computer/dp/0321417461">Prolog
Programming For Artificial Intelligence</a> - 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.</li>
<li><a
href="http://www.amazon.co.uk/Algorithms-Data-Structures-Idioms-Prolog/dp/0136070477">AI
Algorithms, Data Structures and Idioms in Prolog, Lisp and Java</a> - <a
href="https://pdfs.semanticscholar.org/f5c3/d7dbe4c47e310569a14d2338d0cb3d70a1bb.pdf">PDF
here</a></li>
<li><a
href="https://www.cbinsights.com/blog/python-tools-machine-learning/">Python
Tools for Machine Learning</a></li>
<li><a
href="https://wiki.python.org/moin/PythonForArtificialIntelligence">Python
for Artificial Intelligence</a></li>
</ul>
<h2 id="philosophy">Philosophy</h2>
<ul>
<li><a
href="http://www.audible.co.uk/pd/Non-fiction/Superintelligence-Audiobook/B00LPMA33G">Super
Intelligence</a> - Superintelligence asks the question: What happens
when machines surpass humans in general intelligence?</li>
<li><a
href="http://www.audible.co.uk/pd/Non-fiction/Our-Final-Invention-Audiobook/B00KLJMDH8">Our
Final Invention: Artificial Intelligence And The End Of The Human
Era</a> - 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?</li>
<li><a
href="http://www.audible.com/pd/Science-Technology/How-to-Create-a-Mind-Audiobook/B009S7OKJS/ref=a_search_c4_1_1_srTtl?qid=1422483493&amp;sr=1-1">How
to Create a Mind: The Secret of Human Thought Revealed</a> - 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.</li>
<li><a href="http://cogprints.org/7150/1/10.1.1.83.5248.pdf">Minds,
Brains, And Programs</a> - The 1980 paper by philosopher John Searle
that contains the famous ‘Chinese Room’ thought experiment. It is
probably the most famous attack on the notion of a Strong AI possessing
a ‘mind’ or a ‘consciousness’, and it is an interesting reading for
those interested in the intersection of AI and philosophy of mind.</li>
<li><a
href="http://www.amazon.com/G%C3%B6del-Escher-Bach-Eternal-Golden/dp/0465026567">Gödel,
Escher, Bach: An Eternal Golden Braid</a> - Written by Douglas
Hofstadter and taglined “a metaphorical fugue on minds and machines in
the spirit of Lewis Carroll”, this incredible journey into the
fundamental concepts of mathematics, symmetry and intelligence won a
Pulitzer Prize for Non-Fiction in 1979. A major theme throughout is the
emergence of meaning from seemingly ‘meaningless’ elements, like 1’s and
0’s, arranged in special patterns.</li>
<li><a href="https://www.goodreads.com/book/show/34272565-life-3-0">Life
3.0: Being Human in the Age of Artificial Intelligence</a> - 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.</li>
</ul>
<h2 id="free-content">Free Content</h2>
<ul>
<li><a href="http://artint.info/html/ArtInt.html">Foundations Of
Computational Agents</a> - This book is published by Cambridge
University Press</li>
<li><a href="http://ai.stanford.edu/~nilsson/QAI/qai.pdf">The Quest For
Artificial Intelligence</a> - 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.</li>
<li><a href="https://see.stanford.edu/Course/CS229">Stanford CS229 -
Machine Learning</a> - This course provides a broad introduction to
machine learning and statistical pattern recognition.</li>
<li><a
href="http://www.cs.bham.ac.uk/research/projects/poplog/computers-and-thought/">Computers
and Thought: A practical Introduction to Artificial Intelligence</a> -
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.</li>
<li><a href="http://aurellem.org/society-of-mind/index.html">Society of
Mind</a> - Marvin Minsky’s seminal work on how our mind works. Lot of
Symbolic AI concepts have been derived from this basis.</li>
<li><a
href="https://web.archive.org/web/20060627060706/http://www.biosino.org/mirror/www.aaai.org/Press/Books/Hunter/hunter-contents.html">Artificial
Intelligence and Molecular Biology</a> - The current volume is an effort
to bridge that range of exploration, from nucleotide to abstract
concept, in contemporary AI/MB research.</li>
<li><a
href="http://pages.uoregon.edu/moursund/Books/AIBook/index.htm">Brief
Introduction To Educational Implications Of Artificial Intelligence</a>
- 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.</li>
<li><a
href="http://www.scholarpedia.org/article/Encyclopedia:Computational_intelligence">Encyclopedia:
Computational intelligence</a> - Scholarpedia is a peer-reviewed
open-access encyclopedia written and maintained by scholarly experts
from around the world.</li>
<li><a href="http://arxiv.org/abs/1411.1373">Ethical Artificial
Intelligence</a> - a book by Bill Hibbard that combines several
peer-reviewed papers and new material to analyze the issues of ethical
artificial intelligence.</li>
<li><a
href="https://golden.com/wiki/Cluster%3A_Artificial_intelligence">Golden
Artificial Intelligence</a> - a cluster of pages on artificial
intelligence and machine learning.</li>
<li><a href="http://www.r2d3.us/">R2D3</a> - A website with explanations
on topics from Machine Learning to Statistics. All helped with
beautifully animated infographics and real-life examples. Available in
various languages.</li>
<li><a href="https://agentmodels.org/">Modeling Agents with
Probabilistic Programs</a> - This book describes and implements models
of rational agents for (PO)MDPs and Reinforcement Learning.</li>
</ul>
<h2 id="code">Code</h2>
<ul>
<li><a href="https://github.com/explainX/explainx">ExplainX</a>-
ExplainX is a fast, lightweight, and scalable explainable AI framework
for data scientists to explain any black-box model to business
stakeholders.</li>
<li><a href="https://github.com/aimacode">AIMACode</a> - Source code for
“Artificial Intelligence: A Modern Approach” in Common Lisp, Java, and
Python. More to come.</li>
<li><a href="http://leenissen.dk/fann/wp/">FANN</a> - Fast Artificial
Neural Network Library, native for C</li>
<li><a
href="https://github.com/Alex-Linhares/FARGonautica">FARGonautica</a> -
Source code of Douglas Hosftadter’s Fluid Concepts and Creative
Analogies Ph.D. projects.</li>
</ul>
<h2 id="videos">Videos</h2>
<ul>
<li><a href="http://videolectures.net/jul09_hinton_deeplearn">A tutorial
on Deep Learning</a></li>
<li><a
href="http://videolectures.net/rldm2015_littman_computational_reinforcement">Basics
of Computational Reinforcement Learning</a></li>
<li><a
href="http://videolectures.net/rldm2015_silver_reinforcement_learning">Deep
Reinforcement Learning</a></li>
<li><a href="https://youtu.be/7o2GzSj86e8?t=3457">Intelligent agents and
paradigms for AI</a></li>
<li><a href="https://www.youtube.com/watch?v=sc-KbuZqGkI">The
Unreasonable Effectiveness Of Deep Learning</a> - 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</li>
<li><a
href="https://www.manning.com/livevideo/aws-machine-learning-in-motion">AWS
Machine Learning in Motion</a>—This interactive live video course gives
you a crash course in using AWS for machine learning and teaches you how
to build a fully working predictive algorithm.</li>
<li><a
href="https://www.manning.com/livevideo/deep-learning-with-r-in-motion">Deep
Learning with R in Motion</a>-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.</li>
<li><a
href="https://www.manning.com/livevideo/grokking-deep-learning-in-motion">Grokking
Deep Learning in Motion</a>-Grokking Deep Learning in Motion will not
just teach you how to use a single library or framework. You’ll discover
how to build these algorithms from scratch!</li>
<li><a
href="https://www.manning.com/livevideo/reinforcement-learning-in-motion">Reinforcement
Learning in Motion</a> - This live-video breaks down critical concepts
like how RL systems learn, how to sense and process environmental data,
and how to build and train AI agents.</li>
</ul>
<h2 id="learning">Learning</h2>
<ul>
<li><a
href="http://research.microsoft.com/pubs/209355/DeepLearning-NowPublishing-Vol7-SIG-039.pdf">Deep
Learning. Methods And Applications</a> Free book from Microsoft
Research</li>
<li><a href="http://neuralnetworksanddeeplearning.com">Neural Networks
And Deep Learning</a> - Neural networks and deep learning currently
provide the best solutions to many problems in image recognition, speech
recognition, and natural language processing. This book will teach you
the core concepts behind neural networks and deep learning</li>
<li><a
href="http://www.amazon.com/Machine-Learning-Probabilistic-Perspective-Computation/dp/0262018020">Machine
Learning: A Probabilistic Perspective</a> - This textbook offers a
comprehensive and self-contained introduction to the field of machine
learning, based on a unified, probabilistic approach</li>
<li><a href="https://www.deeplearningbook.org">Deep Learning</a> -
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).</li>
<li><a
href="http://www.pyimagesearch.com/2014/09/22/getting-started-deep-learning-python/">Getting
Started with Deep Learning and Python</a></li>
<li><a href="http://machinelearningmastery.com/">Machine Learning
Mastery</a></li>
<li><a
href="https://web.archive.org/web/20201114013453/http://deeplearning.net/">Deep
Learning.net</a> - Aggregation site for DL resources</li>
<li><a
href="https://github.com/josephmisiti/awesome-machine-learning">Awesome
Machine Learning</a> - Like this Github, but ML-focused</li>
<li><a href="http://fastml.com/">FastML</a></li>
<li><a
href="https://github.com/guillaume-chevalier/awesome-deep-learning-resources">Awesome
Deep Learning Resources</a> - Rough list of learning resources for Deep
Learning</li>
<li><a
href="https://freecoursesite.com/?s=Machine+Learning+Data+Science">Professional
and In-Depth Machine Learning Video Courses</a> - A collection of free
professional and in-depth Machine Learning and Data Science video
tutorials and courses</li>
<li><a
href="https://freecoursesite.com/?s=Artificial+Intelligence">Professional
and In-Depth Artificial Intelligence Video Courses</a> - A collection of
free professional and in-depth Artificial Intelligence video tutorials
and courses</li>
<li><a href="https://freecoursesite.com/?s=Deep+Learning">Professional
and In-Depth Deep Learning Video Courses</a> - A collection of free
professional and in-depth Deep Learning video tutorials and courses</li>
<li><a
href="https://developers.google.com/machine-learning/crash-course/ml-intro">Introduction
to Machine Learning</a> - Introductory level machine learning crash
course</li>
<li><a
href="https://github.com/benedekrozemberczki/awesome-graph-classification">Awesome
Graph Classification</a> - Learning from graph structured data</li>
<li><a
href="https://github.com/benedekrozemberczki/awesome-community-detection">Awesome
Community Detection</a> - Clustering graph structured data</li>
<li><a
href="https://github.com/benedekrozemberczki/awesome-decision-tree-papers">Awesome
Decision Tree Papers</a> - Decision tree papers from machine learning
conferences</li>
<li><a
href="https://github.com/benedekrozemberczki/awesome-gradient-boosting-papers">Awesome
Gradient Boosting Papers</a> - Gradient boosting papers from machine
learning conferences</li>
<li><a
href="https://github.com/benedekrozemberczki/awesome-fraud-detection-papers">Awesome
Fraud Detection Papers</a> - Fraud detection papers from machine
learning conferences</li>
<li><a href="https://github.com/crypdick/awesome-neural-art">Awesome
Neural Art</a> - Creating art and manipulating images using deep neural
networks.</li>
</ul>
<h2 id="organizations">Organizations</h2>
<ul>
<li><a href="http://cis.ieee.org/">IEEE Computational Intelligence
Society</a></li>
<li><a href="https://intelligence.org/research-guide/">Machine
Intelligence Research Institute</a></li>
<li><a href="https://openai.com/about/">OpenAI</a></li>
<li><a href="http://www.aaai.org/home.html">Association For The
Advancement of Artificial Intelligence</a></li>
<li><a href="https://deepmind.com/research/">Google DeepMind
Research</a></li>
<li><a href="https://developer.nvidia.com/deep-learning">Nvidia Deep
Learning</a></li>
<li><a href="https://ai.google/">AI Google</a></li>
<li><a href="https://ai.facebook.com">Facebook AI</a></li>
<li><a href="https://www.research.ibm.com/artificial-intelligence">IBM
Research</a></li>
<li><a
href="https://www.microsoft.com/en-us/research/research-area/artificial-intelligence/">Microsoft
Research</a></li>
</ul>
<h2 id="journals">Journals</h2>
<ul>
<li><a href="http://www.springer.com/journal/146">AI &amp;
Society</a></li>
<li><a
href="http://iospress.metapress.com/openurl.asp?genre=journal&amp;issn=0921-7126">AI
Communications</a></li>
<li><a href="http://www.aaai.org/Magazine/magazine.php">AI
Magazine</a></li>
<li><a href="http://www.springer.com/journal/10472">Annals of
Mathematics and Artificial Intelligence</a></li>
<li><a href="http://www.springer.com/journal/200">Applicable Algebra in
Engineering, Communication and Computing</a></li>
<li><a href="https://www.tandfonline.com/toc/uaai20/current">Applied
Artificial Intelligence</a></li>
<li><a href="http://www.springer.com/journal/10489">Applied
Intelligence</a></li>
<li><a
href="http://journals.cambridge.org/action/displayJournal?jid=AIE">Artificial
Intelligence for Engineering Design, Analysis and Manufacturing</a></li>
<li><a href="http://www.springer.com/journal/10462">Artificial
Intelligence Review</a></li>
<li><a href="http://www.elsevier.com/locate/artint">Artificial
Intelligence</a></li>
<li><a href="http://www.springer.com/journal/10515">Automated Software
Engineering</a></li>
<li><a href="http://www.springer.com/journal/10458">Autonomous Agents
and Multi-Agent Systems</a></li>
<li><a href="http://www.springer.com/journal/10588">Computational and
Mathematical Organization Theory</a></li>
<li><a
href="http://www.blackwellpublishing.com/content/BPL_Images/New_Journal_Samples/coin0824-7935~17~4/C.PDF">Computational
Intelligence</a></li>
<li><a href="https://dblp.org/db/journals/etai/index.html">Electronic
Transactions on Artificial Intelligence</a></li>
<li><a href="http://www.springer.com/journal/12065">Evolutionary
Intelligence</a></li>
<li><a
href="http://ieeexplore.ieee.org/servlet/opac?punumber=9670">EXPERT—IEEE
Intelligent Systems</a></li>
<li><a href="http://www.ieee-ras.org/publications/t-ase">IEEE
Transactions Automation Science and Engineering</a></li>
<li><a
href="http://www.springer.com/engineering/robotics/journal/40903">Intelligent
Industrial Systems</a></li>
<li><a
href="https://onlinelibrary.wiley.com/journal/1098111x">International
Journal of Intelligent Systems</a></li>
<li><a
href="https://www.worldscientific.com/worldscinet/ijait">International
Journal on Artificial Intelligence Tools</a></li>
<li><a href="http://www.cs.washington.edu/research/">Journal of
Artificial Intelligence Research</a></li>
<li><a href="http://www.springer.com/journal/10817">Journal of Automated
Reasoning</a></li>
<li><a href="https://www.tandfonline.com/toc/teta20/current">Journal of
Experimental and Theoretical Artificial Intelligence</a></li>
<li><a href="http://www.springer.com/journal/10844">Journal of
Intelligent Information Systems</a></li>
<li><a href="http://www.springer.com/journal/13740">Journal on Data
Semantics</a></li>
<li><a
href="http://journals.cambridge.org/action/displayJournal?jid=KER">Knowledge
Engineering Review</a></li>
<li><a href="http://www.springer.com/journal/11023">Minds and
Machines</a></li>
<li><a href="http://www.springer.com/journal/13748">Progress in
Artificial Intelligence</a></li>
</ul>
<h2 id="competitions">Competitions</h2>
<ul>
<li><a href="https://www.battlecode.org/">MIT Battlecode</a></li>
<li><a href="http://aichallenge.org">AI Challenge</a></li>
<li><a href="http://theaigames.com">AI Games</a></li>
</ul>
<h2 id="newsletters">Newsletters</h2>
<ul>
<li><a href="https://www.superhuman.ai/">Superhuman.ai</a> A daily AI
newsletter</li>
<li><a href="https://alphasignal.ai/">Alpasignal.ai</a> AI newsletter
for developers</li>
<li><a href="https://www.therundown.ai/">Therundown.ai</a> Get the
latest AI news, understand why it matters, and learn how to apply it in
your work.</li>
</ul>
<h2 id="misc">Misc</h2>
<ul>
<li><a href="http://wiki.opencog.org/w/The_Open_Cognition_Project">Open
Cognition Project</a> - We’re undertaking a serious effort to build a
thinking machine</li>
<li><a href="http://aitopics.org/">AITopics</a> - Large aggregation of
AI resources</li>
<li><a href="http://airesources.org/">AIResources</a> - Directory of
open source software and open access data for the AI research
community</li>
<li><a href="https://www.reddit.com/r/artificial/">Artificial
Intelligence Subreddit</a></li>
<li><a href="https://experiments.withgoogle.com/collection/ai">AI
Experiments with Google</a></li>
</ul>
<h2 id="license">License</h2>
<p><a href="http://creativecommons.org/publicdomain/zero/1.0/"><img
src="http://i.creativecommons.org/p/zero/1.0/88x31.png"
alt="CC0" /></a></p>
<p>To the extent possible under law, <a
href="http://owainlewis.com">Owain Lewis</a> has waived all copyright
and related or neighbouring rights to this work.</p>
<p><a
href="https://github.com/owainlewis/awesome-artificial-intelligence">artificialintelligence.md
Github</a></p>