The number after the book name stands for the year in which the book was written in. All books are put in their respective category and are sorted from newest to oldest. π/π before the books show if the book is free or not.
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Algorithms #
Architecture #
Art #
Autobiography #
Awareness #
Basic Income #
Biographies #
Biology #
Business #
Category theory #
Chemistry #
Compilers #
Computational complexity #
Computer graphics #
Computer networking #
Computer science #
Computer Systems #
Creativity #
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Cryptography #
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Data Science #
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Economics #
Engineering #
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Environment #
Fiction #
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Fantasy #
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Short Stories #
Thriller #
Film Making #
Finance #
Fitness #
Functional programming #
Future #
Game Development #
Graphic design #
History #
Alternative history #
Investing #
Kubernetes #
Leadership #
Logic #
Machine learning #
- π Paradigms of artificial intelligence programming (1991)
- π Artificial intelligence a modern approach (1994)
- π Machine learning (1997)
- π The quest for artificial intelligence - a history of ideas and achievements (2009)
- π Introduction to artificial intelligence (2011)
- π Machine learning: a probabilistic perspective (2012)
- π The Nature of Code (2012)
- π Superintelligence: paths, dangers, strategies (2014)
- π Understanding machine learning: from theory to algorithms (2014)
- π Neural Networks and Deep Learning (2015)
- π Deep Larning with Python (2017)
- π Tensorflow machine learning cookbook (2017)
- π Hands-On Machine Learning with Scikit-Learn and TensorFlow (2017)
- π Machine Learning with Go (2017) - Build simple, maintainable, and easy to deploy machine learning applications.
- π Interpretable Machine Learning (2018)
- π Deep learning
- π Interpretable machine learning (2018) - Explaining the decisions and behavior of machine learning models.
- π How Machine Learning Works (2019)- An introduction to both ML's practice and math foundations in a non-threatning approach.
- π Grokking Deep Learning (2019)
- π MachineLearningWithTensorFlow2ed (2020) - 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.
- π Machine Learning Bookcamp (2020) - Project-based approach to learning machine learning.
Management #
Math #
Memoirs #
Mindset #
Minimalism #
Music production #
Neuroscience #
Non Fiction #
Nutrition #
Operating Systems #
iOS #
Linux #
MacOS #
Philosophy #
Physics #
Poetry #
Politics #
Programming interviews #
Programming language design #
Programming languages #
Assembly #
C++ #
Clojure #
Go #
Haskell #
Java #
JavaScript #
Kotlin #
Lisp #
OCaml #
Perl #
PowerShell #
Prolog #
Purescript #
Python #
ReasonML #
Ruby #
Rust #
Scala #
Smalltalk #
Swift #
TypeScript #
Agda #
Programming #
Psychedelics #
Psychology #
Quantum physics #
Regular Expressions #
Reinforcement learning #
Reverse engineering #
Science #
Scifi #
SciFi Series #
Security #
Sleep #
Society #
Spirituality #
Startups #
Statistics #
Strategy #
Text editors #
Vim #
Type theory #
Unix #
Version control #
Git #
Visualization #
Writing #
Web Development #
CSS #
Node #
React #
Redux #
Webpack #
Web design #
Other #




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