Ecosyste.ms: Awesome
An open API service indexing awesome lists of open source software.
awesome-AI-books
Some awesome AI related books and pdfs for learning and downloading, also apply some playground models for learning
https://github.com/zslucky/awesome-AI-books
- arxiv.org
- Science
- Nature
- DeepMind Publications
- OpenAI Research
- OpenAI Gym
- malmo
- DeepMind Pysc2
- Procgen - Generated Game-Like Gym-Environments.
- TorchCraftAI
- Valve Dota2 - cn))
- Mario AI Framework
- Google Dopamine
- TextWorld - A learning environment sandbox for training and testing reinforcement learning (RL) agents on text-based games.
- Mini Grid
- MAgent - agent Reinforcement Learning
- XWorld
- Neural MMO
- MinAtar
- craft-env
- gym-sokoban
- Pommerman
- gym-miniworld
- vizdoomgym - based AI Research Platform for Reinforcement Learning from Raw Visual Information) enviroments.
- ddz-ai
- Artificial Intelligence-A Modern Approach (3rd Edition) - Stuart Russell & peter Norvig
- Grokking Artificial Intelligence Algorithms - Rishal Hurbans
- 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
- 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
- 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](https://github.com/zslucky/awesome-AI-books/tree/master/resources/Machine%20Learning%20for%20OpenCV))
- 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
- Dive into Deep Learning - (Using MXNet)An interactive deep learning book with code, math, and discussions.
- d2l-pytorch - (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
- Interpretable AI - Ajay Thampi
- Conversational AI - Andrew R. Freed
- 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
- Quantum Computing Primer - D-Wave quantum computing primer
- Quantum computing 101 - Quantum computing 101, from University of Waterloo
- pdf - Nielsen
- pdf - 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 - ProjectQ is an open source effort for quantum computing.
- Stable Diffusion - [[Paper](https://arxiv.org/abs/2112.10752)] A latent text-to-image diffusion model
- Stable Diffusion V2 - High-Resolution Image Synthesis with Latent Diffusion Models
- GFPGAN - [[Paper](https://arxiv.org/abs/2101.04061)] GFPGAN aims at developing Practical Algorithms for Real-world Face Restoration.
- ESRGAN - [[Paper](https://arxiv.org/abs/2107.10833)] ECCV18 Workshops - Enhanced SRGAN. Champion PIRM Challenge on Perceptual Super-Resolution. The training codes are in BasicSR.
- CodeFormer - [[Paper](https://arxiv.org/abs/2206.11253)] - [NeurIPS 2022] Towards Robust Blind Face Restoration with Codebook Lookup Transformer
- UniPC - [[Paper](https://arxiv.org/abs/2302.04867)] UniPC: A Unified Predictor-Corrector Framework for Fast Sampling of Diffusion Models
- A3C - Google DeepMind Asynchronous Advantage Actor-Critic algorithm
- Q-Learning - media/dqn/DQNNaturePaper.pdf) [DDQN](https://arxiv.org/pdf/1509.06461.pdf) - 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 [Github](https://github.com/jundongl/scikit-feature)
- Scikit learn - Machine Learning in Python.
- Linfa - spirit of `scikit learn`, 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 - Some model stacking algorithms implemented in this lib.
- RGF - Learning Nonlinear Functions Using `Regularized Greedy Forest` (multi-core implementation [FastRGF](https://github.com/RGF-team/rgf/tree/master/FastRGF))
- FM - Factorization Machines and some extended Algorithms
- GNN Papers - Must-read papers on graph neural networks (GNN)
- EfficientNet - Rethinking Model Scaling for Convolutional Neural Networks
- DenseNet - Densely Connected Convolutional Networks
- XLNet - [repo](https://github.com/zihangdai/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 - Google Model search (MS) is a framework that implements AutoML algorithms for model architecture search at scale.
- TPOT - 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 [WEKA](https://www.cs.waikato.ac.nz/ml/weka/).
- MLBox - MLBox is a powerful Automated Machine Learning python library
- ZenML - ZenML is built for ML practitioners who are ramping up their ML workflows towards production
- t-SNE - linear/Non-params**) - T-distributed Stochastic Neighbor Embedding (t-SNE) is a machine learning algorithm for visualization
- PCA - Principal component analysis
- LDA - Linear Discriminant Analysis
- LLE - linear**) - Locally linear embedding
- Laplacian Eigenmaps - Laplacian Eigenmaps for Dimensionality Reduction and Data Representation
- Sammon Mapping - linear**) - Sammon mapping is designed to minimise the differences between corresponding inter-point distances in the
- Pandas - Flexible and powerful data analysis / manipulation library for Python.
- Polars - Lightning-fast DataFrame library for Rust and Python.
- 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.
- btc-clean-qrcode
- eth-clean-qrcode
Programming Languages
Keywords
deep-learning
6
pytorch
5
reinforcement-learning
5
machine-learning
5
python
4
data-science
4
super-resolution
2
distributed
2
mxnet
2
face-restoration
2
automl
2
automated-machine-learning
2
rust
2
tensorflow
2
keras
2
quantum-programming-language
1
gan
1
gfpgan
1
image-restoration
1
quantum-computing
1
esrgan
1
codebook
1
codeformer
1
face-enhancement
1
restoration
1
vqgan
1
algorithms
1
scientific-computing
1
gnn
1
paper-list
1
ai
1
google
1
ml
1
rl
1
text-based-adventure
1
text-based-game
1
multi-agent
1
simulator
1
paper
1
environment
1
gym
1
openai
1
sokoban
1
openai-gym
1
openai-gym-environments
1
vizdoom
1
book
1
computer-vision
1
d2l
1
dive-into-deep-learning
1