Awesome AI books
Some awesome AI related books and pdfs for downloading and learning.
Preface
This repo only used for learning, do not use in business.
Welcome for providing great books in this repo or tell me which great book you need and I will try to append it in this repo, any idea you can create issue or PR here.
Due to github Large file storage limition, all books pdf stored in Yandex.Disk.
Some often used Mathematic Symbols can refer this page
Content
 Organization with papers/researchs
 Training ground
 Books
 Quantum with AI
 Libs With Online Books
 Distributed training
Organization with papers/researchs
Training ground
 OpenAI Gym: A toolkit for developing and comparing reinforcement learning algorithms. (Can play with Atari, Box2d, MuJoCo etc...)
 malmo: Project Malmö is a platform for Artificial Intelligence experimentation and research built on top of Minecraft.
 DeepMind Pysc2: StarCraft II Learning Environment.
 Procgen: Procgen Benchmark: ProcedurallyGenerated GameLike GymEnvironments.
 TorchCraftAI: A bot platform for machine learning research on StarCraft®: Brood War®
 Valve Dota2: Dota2 game acessing api. (CN doc)
 Mario AI Framework: A Mario AI framework for using AI methods.
 Google Dopamine: Dopamine is a research framework for fast prototyping of reinforcement learning algorithms
 TextWorld: Microsoft  A learning environment sandbox for training and testing reinforcement learning (RL) agents on textbased games.
 Mini Grid: Minimalistic gridworld environment for OpenAI Gym
 MAgent: A Platform for Manyagent Reinforcement Learning
 XWorld: A C++/Python simulator package for reinforcement learning
 Neural MMO: A Massively Multiagent Game Environment
 MinAtar: MinAtar is a testbed for AI agents which implements miniaturized version of several Atari 2600 games.
 craftenv: CraftEnv is a 2D crafting environment
 gymsokoban: Sokoban is Japanese for warehouse keeper and a traditional video game
 Pommerman Playground hosts Pommerman, a clone of Bomberman built for AI research.
 gymminiworld MiniWorld is a minimalistic 3D interior environment simulator for reinforcement learning & robotics research
 vizdoomgym OpenAI Gym wrapper for ViZDoom (A Doombased AI Research Platform for Reinforcement Learning from Raw Visual Information) enviroments.
 ddzai 以孤立语假设和宽度优先搜索为基础，构建了一种多通道堆叠注意力Transformer结构的斗地主ai
Books
Introductory theory and get start
 Artificial IntelligenceA Modern Approach (3rd Edition)  Stuart Russell & peter Norvig
 COMMERCIAL Grokking Artificial Intelligence Algorithms  Rishal Hurbans
Mathematics
 A First Course in ProbabilityA First Course in Probability (8th)  Sheldon M Ross
 Convex Optimization  Stephen Boyd
 Elements of Information Theory Elements  Thomas Cover & Jay A Thomas
 Discrete Mathematics and Its Applications 7th  Kenneth H. Rosen
 Introduction to Linear Algebra (5th)  Gilbert Strang
 Linear Algebra and Its Applications (5th)  David C Lay
 Probability Theory The Logic of Science  Edwin Thompson Jaynes
 Probability and Statistics 4th  Morris H. DeGroot
 Statistical Inference (2nd)  Roger Casella
 信息论基础 (原书Elements of Information Theory Elements第2版)  Thomas Cover & Jay A Thomas
 凸优化 (原书Convex Optimization)  Stephen Boyd
 数理统计学教程  陈希儒
 数学之美 2th  吴军
 概率论基础教程 (原书A First Course in ProbabilityA First Course in Probability第9版)  Sheldon M Ross
 线性代数及其应用 (原书Linear Algebra and Its Applications第3版)  David C Lay
 统计推断 (原书Statistical Inference第二版)  Roger Casella
 离散数学及其应用 (原书Discrete Mathematics and Its Applications第7版)  Kenneth H.Rosen
Data mining
 Introduction to Data Mining  PangNing Tan
 Programming Collective Intelligence  Toby Segaran
 Feature Engineering for Machine Learning  Amanda Casari, Alice Zheng
 集体智慧编程  Toby Segaran
Machine Learning
 Information Theory, Inference and Learning Algorithms  David J C MacKay
 Machine Learning  Tom M. Mitchell
 Pattern Recognition and Machine Learning  Christopher Bishop
 The Elements of Statistical Learning  Trevor Hastie
 Machine Learning for OpenCV  Michael Beyeler (Source code here)
 机器学习  周志华
 机器学习 (原书Machine Learning)  Tom M. Mitchell
 统计学习方法  李航
Deep Learning
 Online Quick learning
 Dive into Deep Learning  (Using MXNet)An interactive deep learning book with code, math, and discussions.
 d2lpytorch  (Dive into Deep Learning) pytorch version.
 动手学深度学习  (Dive into Deep Learning) for chinese.
 Deep Learning  Ian Goodfellow & Yoshua Bengio & Aaron Courville
 Deep Learning Methods and Applications  Li Deng & Dong Yu
 Learning Deep Architectures for AI  Yoshua Bengio
 Machine Learning An Algorithmic Perspective (2nd)  Stephen Marsland
 Neural Network Design (2nd)  Martin Hagan
 Neural Networks and Learning Machines (3rd)  Simon Haykin
 Neural Networks for Applied Sciences and Engineering  Sandhya Samarasinghe
 深度学习 (原书Deep Learning)  Ian Goodfellow & Yoshua Bengio & Aaron Courville
 神经网络与机器学习 (原书Neural Networks and Learning Machines)  Simon Haykin
 神经网络设计 (原书Neural Network Design)  Martin Hagan
 COMMERCIAL Interpretable AI  Ajay Thampi
 COMMERCIAL Conversational AI  Andrew R. Freed
Philosophy
 COMMERCIAL Human Compatible: Artificial Intelligence and the Problem of Control  Stuart Russell
 COMMERCIAL Life 3.0: Being Human in the Age of Artificial Intelligence  Max Tegmark
 COMMERCIAL Superintelligence: Paths, Dangers, Strategies  Nick Bostrom
Quantum with AI

Quantum Basic
 Quantum Computing Primer  DWave quantum computing primer
 Quantum computing 101  Quantum computing 101, from University of Waterloo
 pdf Quantum Computation and Quantum Information  Nielsen
 pdf 量子计算和量子信息（量子计算部分） Nielsen

Quantum AI

Quantum Related Framework
 ProjectQ  ProjectQ is an open source effort for quantum computing.
Libs With Online Books

Reinforcement Learning
 A3C  Google DeepMind Asynchronous Advantage ActorCritic algorithm
 QLearning SARSA DQN DDQN  QLearning is a valuebased Reinforcement Learning algorithm
 DDPG  Deep Deterministic Policy Gradient,
 LargeScale Curiosity  LargeScale Study of CuriosityDriven Learning
 PPO  OpenAI Proximal Policy Optimization Algorithms
 RND  OpenAI Random Network Distillation, an exploration bonus for deep reinforcement learning method.
 VIME  OpenAI Variational Information Maximizing Exploration
 DQV  Deep QualityValue (DQV) Learning
 ERL  EvolutionGuided Policy Gradient in Reinforcement Learning
 MF MultiAgent RL  Mean Field MultiAgent Reinforcement Learning. (this paper include MFQ and MFAC)
 MAAC  ActorAttentionCritic for MultiAgent Reinforcement Learning

Feature Selection
 scikitfeature  A collection of feature selection algorithms, available on Github

Machine Learning
 Xgboost (Python, R, JVM, Julia, CLI)  Xgboost lib's document.
 LightGBM (Python, R, CLI)  Microsoft lightGBM lib's features document.
 CatBoost (Python, R, CLI)  Yandex Catboost lib's key algorithm pdf papper.
 StackNet (Java, CLI)  Some model stacking algorithms implemented in this lib.
 RGF  Learning Nonlinear Functions Using
Regularized Greedy Forest
(multicore implementation FastRGF)  FM, FastFM, FFM, XDeepFM  Factorization Machines and some extended Algorithms

Deep Learning
 GNN Papers  Mustread papers on graph neural networks (GNN)
 EfficientNet  Rethinking Model Scaling for Convolutional Neural Networks
 DenseNet  Densely Connected Convolutional Networks

NLP

CV
 Fast RCNN  Fast Regionbased Convolutional Network method (Fast RCNN) for object detection
 Mask RCNN  Mask RCNN, extends Faster RCNN by adding a branch for predicting an object mask in parallel with the existing branch for bounding box recognition.
 GQN  DeepMind Generative Query Network, Neural scene representation and rendering

Meta Learning
 MAML  ModelAgnostic MetaLearning for Fast Adaptation of Deep Networks

Transfer Learning
 GCN  Zeroshot Recognition via Semantic Embeddings and Knowledge Graphs

Auto ML
 Model Search (Python)  Google Model search (MS) is a framework that implements AutoML algorithms for model architecture search at scale.
 TPOT (Python)  TPOT is a lib for AutoML.
 Autosklearn (Python)  autosklearn is an automated machine learning toolkit and a dropin replacement for a scikitlearn estimator
 AutoKeras (Python)  AutoKeras is an open source software library for automated machine learning (AutoML). It is developed by DATA Lab
 TransmogrifAI (JVM)  TransmogrifAI (pronounced trănsmŏgˈrəfī) is an AutoML library written in Scala that runs on top of Spark
 AutoWEKAA  Provides automatic selection of models and hyperparameters for WEKA.
 MLBox (Python)  MLBox is a powerful Automated Machine Learning python library

Pipeline Training
 ZenML (Python)  ZenML is built for ML practitioners who are ramping up their ML workflows towards production

Dimensionality Reduction
 tSNE (Nonlinear/Nonparams)  Tdistributed Stochastic Neighbor Embedding (tSNE) is a machine learning algorithm for visualization
 PCA (Linear)  Principal component analysis
 LDA (Linear)  Linear Discriminant Analysis
 LLE (Nonlinear)  Locally linear embedding
 Laplacian Eigenmaps  Laplacian Eigenmaps for Dimensionality Reduction and Data Representation
 Sammon Mapping (Nonlinear)  Sammon mapping is designed to minimise the differences between corresponding interpoint distances in the two spaces
Distributed training
 Horovod  Horovod is a distributed training framework for TensorFlow, Keras, PyTorch, and MXNet. The goal of Horovod is to make distributed Deep Learning fast and easy to use.
 Acme  A Research Framework for (Distributed) Reinforcement Learning.
 bagua  Bagua is a flexible and performant distributed training algorithm development framework.
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