awesome-AI-books
Some awesome AI related books and pdfs for learning and downloading, also apply some playground models for learning
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aialgorithmsartificial-intelligencebooksdata-miningdeep-learninglearningmachine-learningmathematicspdfplaygroundquantum-algorithmsquantum-computingquantum-informationreadingreinforcement-learning
Awesome AI books / Content | |||
| Organization with papers/researchs | 1,277 | over 1 year ago | |
| Training ground | 1,277 | over 1 year ago | |
| Books | 1,277 | over 1 year ago | |
Awesome AI books / Content / Books | |||
| Introductory theory and get start | 1,277 | over 1 year ago | |
| Mathematics | 1,277 | over 1 year ago | |
| Data mining | 1,277 | over 1 year ago | |
| Deep Learning | 1,277 | over 1 year ago | |
| Philosophy | 1,277 | over 1 year ago | |
Awesome AI books / Content | |||
| Quantum with AI | 1,277 | over 1 year ago | |
Awesome AI books / Content / Quantum with AI | |||
| Quantum Basic | 1,277 | over 1 year ago | |
| Quantum AI | 1,277 | over 1 year ago | |
| Quantum Related Framework | 1,277 | over 1 year ago | |
Awesome AI books / Content | |||
| Libs With Online Books | 1,277 | over 1 year ago | |
Awesome AI books / Content / Libs With Online Books | |||
| Reinforcement Learning | 1,277 | over 1 year ago | |
| Feature Selection | 1,277 | over 1 year ago | |
| Machine Learning | 1,277 | over 1 year ago | |
| Deep Learning | 1,277 | over 1 year ago | |
| NLP | 1,277 | over 1 year ago | |
| CV | 1,277 | over 1 year ago | |
| Meta Learning | 1,277 | over 1 year ago | |
| Transfer Learning | 1,277 | over 1 year ago | |
| Auto ML | 1,277 | over 1 year ago | |
| Dimensionality Reduction | 1,277 | over 1 year ago | |
Awesome AI books / Content | |||
| Distributed training | 1,277 | over 1 year ago | |
Awesome AI books / Organization with papers/researchs | |||
| arxiv.org | |||
| Science | |||
| Nature | |||
| DeepMind Publications | |||
| OpenAI Research | |||
Awesome AI books / Training ground | |||
| OpenAI Gym | : A toolkit for developing and comparing reinforcement learning algorithms. (Can play with , Box2d, MuJoCo etc...) | ||
| malmo | 4,065 | 10 months ago | : Project Malmö is a platform for Artificial Intelligence experimentation and research built on top of Minecraft |
| DeepMind Pysc2 | 7,996 | 2 months ago | : StarCraft II Learning Environment |
| Procgen | 999 | 9 months ago | : Procgen Benchmark: Procedurally-Generated Game-Like Gym-Environments |
| TorchCraftAI | : A bot platform for machine learning research on StarCraft®: Brood War® | ||
| Valve Dota2 | : Dota2 game acessing api. ( ) | ||
| Mario AI Framework | 96 | 11 months ago | : A Mario AI framework for using AI methods |
| Google Dopamine | 10,449 | 5 months ago | : Dopamine is a research framework for fast prototyping of reinforcement learning algorithms |
| TextWorld | 1,197 | 2 months ago | : Microsoft - A learning environment sandbox for training and testing reinforcement learning (RL) agents on text-based games |
| Mini Grid | 2,086 | 25 days ago | : Minimalistic gridworld environment for OpenAI Gym |
| MAgent | 1,685 | almost 2 years ago | : A Platform for Many-agent Reinforcement Learning |
| XWorld | 85 | over 5 years ago | : A C++/Python simulator package for reinforcement learning |
| Neural MMO | 1,582 | about 1 year ago | : A Massively Multiagent Game Environment |
| MinAtar | 282 | over 1 year ago | : MinAtar is a testbed for AI agents which implements miniaturized version of several Atari 2600 games |
| craft-env | 44 | almost 6 years ago | : CraftEnv is a 2D crafting environment |
| gym-sokoban | 322 | 11 months ago | : Sokoban is Japanese for warehouse keeper and a traditional video game |
| Pommerman | 765 | 9 months ago | Playground hosts Pommerman, a clone of Bomberman built for AI research |
| gym-miniworld | 694 | 25 days ago | MiniWorld is a minimalistic 3D interior environment simulator for reinforcement learning & robotics research |
| vizdoomgym | 65 | about 3 years ago | OpenAI Gym wrapper for (A Doom-based AI Research Platform for Reinforcement Learning from Raw Visual Information) enviroments |
| ddz-ai | 90 | over 3 years ago | 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 |
Awesome AI books / Books / Introductory theory and get start | |||
| Artificial Intelligence-A Modern Approach (3rd Edition) | Stuart Russell & peter Norvig | ||
| Grokking Artificial Intelligence Algorithms | Rishal Hurbans | ||
Awesome AI books / Books / 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 | ||
Awesome AI books / Books / Data mining | |||
| Introduction to Data Mining | Pang-Ning Tan | ||
| Programming Collective Intelligence | Toby Segaran | ||
| Feature Engineering for Machine Learning | Amanda Casari, Alice Zheng | ||
| 集体智慧编程 | Toby Segaran | ||
Awesome AI books / Books / 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 ( ) | ||
| 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 | ||
Awesome AI books / Books / Deep Learning / Online Quick learning | |||
| Dive into Deep Learning | (Using MXNet)An interactive deep learning book with code, math, and discussions | ||
| d2l-pytorch | 4,221 | 2 months ago | (Dive into Deep Learning) pytorch version |
| 动手学深度学习 | (Dive into Deep Learning) for chinese | ||
Awesome AI books / Books / Deep Learning | |||
| 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 | ||
| Interpretable AI | Ajay Thampi | ||
| Conversational AI | Andrew R. Freed | ||
Awesome AI books / Books / Philosophy | |||
| Human Compatible: Artificial Intelligence and the Problem of Control | Stuart Russell | ||
| Life 3.0: Being Human in the Age of Artificial Intelligence | Max Tegmark | ||
| Superintelligence: Paths, Dangers, Strategies | Nick Bostrom | ||
Awesome AI books / Quantum with AI | |||
| Quantum Computing Primer | D-Wave quantum computing primer | ||
| Quantum computing 101 | Quantum computing 101, from University of Waterloo | ||
| Quantum Computation and Quantum Information - Nielsen | |||
| 量子计算和量子信息（量子计算部分）- Nielsen | |||
| Quantum neural networks | |||
| An Artificial Neuron Implemented on an Actual Quantum Processor | |||
| Classification with Quantum Neural Networks on Near Term Processors | |||
| Black Holes as Brains: Neural Networks with Area Law Entropy | |||
| ProjectQ | 879 | 26 days ago | ProjectQ is an open source effort for quantum computing |
Awesome AI books / Libs With Online Books | |||
| Stable Diffusion | 67,640 | 3 months ago | [ ] A latent text-to-image diffusion model |
| Stable Diffusion V2 | 38,588 | 8 days ago | High-Resolution Image Synthesis with Latent Diffusion Models |
| GFPGAN | 35,542 | 2 months ago | [ ] GFPGAN aims at developing Practical Algorithms for Real-world Face Restoration |
| ESRGAN | 5,947 | almost 2 years ago | [ ] ECCV18 Workshops - Enhanced SRGAN. Champion PIRM Challenge on Perceptual Super-Resolution. The training codes are in BasicSR |
| CodeFormer | 15,017 | about 2 months ago | [ ] - [NeurIPS 2022] Towards Robust Blind Face Restoration with Codebook Lookup Transformer |
| UniPC | 291 | about 1 year ago | [ ] UniPC: A Unified Predictor-Corrector Framework for Fast Sampling of Diffusion Models |
| A3C | Google DeepMind Asynchronous Advantage Actor-Critic algorithm | ||
| Q-Learning | SARSA - Q-Learning is a value-based Reinforcement Learning algorithm | ||
| DDPG | Deep Deterministic Policy Gradient, | ||
| Large-Scale Curiosity | Large-Scale Study of Curiosity-Driven 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 Quality-Value (DQV) Learning | ||
| ERL | Evolution-Guided Policy Gradient in Reinforcement Learning | ||
| MF Multi-Agent RL | Mean Field Multi-Agent Reinforcement Learning. (this paper include MF-Q and MF-AC) | ||
| MAAC | Actor-Attention-Critic for Multi-Agent Reinforcement Learning | ||
| scikit-feature | A collection of feature selection algorithms, available on | ||
| Scikit learn | ( ) - Machine Learning in Python | ||
| Linfa | 3,675 | about 1 month ago | ( ) - spirit of , a rust ML lib |
| Xgboost | ( ) - Xgboost lib's document | ||
| LightGBM | ( ) - Microsoft lightGBM lib's features document | ||
| CatBoost | ( ) - Yandex Catboost lib's key algorithm pdf papper | ||
| StackNet | 1,321 | about 6 years ago | ( ) - Some model stacking algorithms implemented in this lib |
| RGF | Learning Nonlinear Functions Using (multi-core implementation ) | ||
| FM | , , , - Factorization Machines and some extended Algorithms | ||
| GNN Papers | 15,875 | 9 months ago | Must-read papers on graph neural networks (GNN) |
| EfficientNet | Rethinking Model Scaling for Convolutional Neural Networks | ||
| DenseNet | Densely Connected Convolutional Networks | ||
| XLNet | XLNet: Generalized Autoregressive Pretraining for Language Understanding | ||
| BERT | Pre-training of Deep Bidirectional Transformers for Language Understanding | ||
| GPT-3 | Language Models are Few-Shot Learners | ||
| Fast R-CNN | Fast Region-based Convolutional Network method (Fast R-CNN) for object detection | ||
| Mask R-CNN | Mask R-CNN, extends Faster R-CNN 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 | ||
| MAML | Model-Agnostic Meta-Learning for Fast Adaptation of Deep Networks | ||
| GCN | Zero-shot Recognition via Semantic Embeddings and Knowledge Graphs | ||
| Model Search | 3,264 | about 2 months ago | ( ) - Google Model search (MS) is a framework that implements AutoML algorithms for model architecture search at scale |
| TPOT | 9,663 | 2 months ago | ( ) - TPOT is a lib for AutoML |
| Auto-sklearn | ( ) - auto-sklearn is an automated machine learning toolkit and a drop-in replacement for a scikit-learn estimator | ||
| Auto-Keras | ( ) - Auto-Keras is an open source software library for automated machine learning (AutoML). It is developed by DATA Lab | ||
| TransmogrifAI | ( ) - TransmogrifAI (pronounced trăns-mŏgˈrə-fī) is an AutoML library written in Scala that runs on top of Spark | ||
| Auto-WEKAA | Provides automatic selection of models and hyperparameters for | ||
| MLBox | 1,490 | about 1 year ago | ( ) - MLBox is a powerful Automated Machine Learning python library |
| ZenML | 3,957 | 1 day ago | ( ) - ZenML is built for ML practitioners who are ramping up their ML workflows towards production |
| t-SNE | ( ) - T-distributed Stochastic Neighbor Embedding (t-SNE) is a machine learning algorithm for visualization | ||
| PCA | ( ) - Principal component analysis | ||
| LDA | ( ) - Linear Discriminant Analysis | ||
| LLE | ( ) - Locally linear embedding | ||
| Laplacian Eigenmaps | Laplacian Eigenmaps for Dimensionality Reduction and Data Representation | ||
| Sammon Mapping | ( ) - Sammon mapping is designed to minimise the differences between corresponding inter-point distances in the two spaces | ||
| Pandas | 43,367 | 2 days ago | ( ) - Flexible and powerful data analysis / manipulation library for Python |
| Polars | 29,300 | 10 days ago | ( ) - Lightning-fast DataFrame library for Rust and Python |
Awesome AI books / Distributed training | |||
| Horovod | 14,163 | 28 days ago | 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 | 3,471 | 11 days ago | A Research Framework for (Distributed) Reinforcement Learning |
| bagua | 873 | about 2 months ago | Bagua is a flexible and performant distributed training algorithm development framework |
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