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A curated list of Artificial Intelligence (AI) courses, books, video lectures and papers.

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Awesome Artificial Intelligence (AI) Awesome

A curated list of Artificial Intelligence (AI) courses, books, video lectures and papers.

Contributions most welcome.

Contents

  1. Courses
  2. Books
  3. Programming
  4. Philosophy
  5. Free Content
  6. Code
  7. Videos
  8. Learning
  9. Organizations
  10. Journals
  11. Competitions
  12. Newsletters
  13. Misc

Courses

Books

  • Machine Learning for Mortals (Mere and Otherwise) - Early access book that provides basics of machine learning and using R programming language.
  • How Machine Learning Works - Mostafa Samir. Early access book that introduces machine learning from both practical and theoretical aspects in a non-threating way.
  • MachineLearningWithTensorFlow2ed - a book on general purpose machine learning techniques regression, classification, unsupervised clustering, reinforcement learning, auto encoders, convolutional neural networks, RNNs, LSTMs, using TensorFlow 1.14.1.
  • Serverless Machine Learning - 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.
  • The Hundred-Page Machine Learning Book - 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.
  • AI-Powered Search - a book that teaches you how to build search engines that automatically understand the intention of a query in order to deliver significantly better results.
  • Grokking Machine Learning - Grokking Machine Learning teaches you how to apply ML to your projects using only standard Python code and high school-level math.
  • Machine Learning Bookcamp - Learn the essentials of machine learning by completing a carefully designed set of real-world projects.
  • Interpretable AI - a hands-on guide to interpretability techniques that open up the black box of AI.
  • Conversational AI - Design, develop, and deploy human-like AI solutions that chat with your customers, solve their problems, and streamline your support services.
  • Deep Learning Patterns and Practices - Discover best practices, reproducible architectures, and design patterns to help guide deep learning models from the lab into production.
  • Feature Engineering Bookcamp - This book’s practical case-studies reveal feature engineering techniques that upgrade your data wrangling—and your ML results.
  • Build a Robo Advisor with Python (From Scratch) - A book about how to construct a Python-based financial advisor of your own.
  • Regular Expression Puzzles and AI Coding Assistants - A book about using ChatGPT and GitHub Copilot for coding.
  • The Complete Obsolete Guide to Generative AI -This book gives you the tools you need to work better, faster, and smarter with AI.
  • AI-Assisted Data Science -A book that teaches how to use a new generation of AI assistants and Large Language Models (LLMs) to simplify and accelerate common data science tasks.
  • AI Reality and Illusion -A comprehensive guide to every leading technique of AI and machine learning, showing you how they work, and how you can incorporate them into your business.

Programming

Philosophy

  • 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.
  • Minds, Brains, And Programs - The 1980 paper by philospher John Searle that contains the famous 'Chinese Room' thought experiment. Probably the most famous attack on the notion of a Strong AI possessing a 'mind' or a 'consciousness', and interesting reading for those interested in the intersection of AI and philosophy of mind.
  • Gödel, Escher, Bach: An Eternal Golden Braid - Written by Douglas Hofstadter and taglined "a metaphorical fugue on minds and machines in the spirit of Lewis Carroll", this wonderful journey into the the fundamental concepts of mathematics,symmetry and intelligence won a Pulitzer Price 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.
  • 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.

Free Content

Code

  • ExplainX- ExplainX is a fast, light-weight, and scalable explainable AI framework for data scientists to explain any black-box model to business stakeholders.
  • AIMACode - Source code for "Artificial Intelligence: A Modern Approach" in Common Lisp, Java, Python. More to come.
  • FANN - Fast Artificial Neural Network Library, native for C
  • FARGonautica - Source code of Douglas Hosftadter's Fluid Concepts and Creative Analogies Ph.D. projects.

Videos

Learning

Organizations

Journals

Competitions

Newsletters

  • AI Digest. A weekly newsletter to keep up to date with AI, machine learning, and data science. Archive.

Misc

License

CC0

To the extent possible under law, Owain Lewis has waived all copyright and related or neighboring rights to this work.

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