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Hands-on ML - a series of Jupyter notebooks that walk you through the fundamentals of Machine Learning and Deep Learning in python using Scikit-Learn and TensorFlow.
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Image Classification - an absolute beginner's guide to Machine Learning and Image Classification with Neural Networks
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Image Classification with 5 methods - compared performance of KNN, SVM, BPNN, CNN, Transfer Learning (retrain on Inception v3) on image classification problem. CNN is implemented with TensorFlow
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Learn text analytics - learn how to process, classify, cluster, summarize, understand syntax, semantics and sentiment of text data
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A complete daily plan for studying to become a machine learning engineer.
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Dive into Machine Learning with Python Jupyter notebook and scikit-learn
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Data science Python notebooks - Deep learning (TensorFlow, Theano, Caffe, Keras), scikit-learn, Kaggle, big data (Spark, Hadoop MapReduce, HDFS), matplotlib, pandas, NumPy, SciPy, Python essentials, AWS, and various command lines
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ML from scratch - Python implementations of Machine Learning models and algorithms from scratch. Aims to cover everything from Data Mining techniques to Deep Learning.
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ML algorithms - Minimal and clean examples of machine learning algorithms
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Sonnet - a library built on top of TensorFlow for building complex neural networks
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Tensorpack - a training interface based on TensorFlow
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Edward - Python library for probabilistic modeling, inference, and criticism, it fuses three fields: Bayesian statistics and machine learning, deep learning, and probabilistic programming
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SVM paper - math behind SVMs
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Thundersvm - a fast SVM Library on GPUs and CPUs
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TFLearn - deep learning library featuring a higher-level API for TensorFlow
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Neural-doodle - turn your two-bit doodles into fine artworks with deep neural networks (an implementation of Semantic Style Transfer)
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DL with Scikit - Deep neural networks without the learning cliff! Classifiers and regressors compatible with scikit-learn.
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DEvol - Deep Neural Network Evolution utilizes genetic programming to automatically architect a deep neural network with optimal hyperparameters for a given dataset using Keras.
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Neural storyteller - a recurrent neural network for generating little stories about images
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Char RNN with Tensorflow - multi-layer RNNs (LSTM, RNN) for character-level language models in Python using Tensorflow
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Char RNN with Torch - multi-layer RNNs (LSTM, GRU, RNN) for character-level language models in Torch
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Torch RNNs - efficient, reusable RNNs and LSTMs for Torch
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NeuralTalk - Python + numpy project for learning Multimodal Recurrent Neural Networks that describe images with sentences.
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Biaxial rnn music composition - a recurrent neural network designed to generate classical music.
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Conditional Random Fields as Recurrent Neural Networks - semantic image segmentation method described.
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Word level RNN with tensorflow - multi-layer Recurrent Neural Networks (LSTM, RNN) for word-level language models in Python using TensorFlow.
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LSTM code - minimal, clean example of LSTM neural network training in python, for learning purposes.
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LSTM paper - paper explaining reasoning behind using LSTMs.
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LSTM for Time Series Prediction - - LSTM built using Keras Python package to predict time series steps and sequences. Includes sin wave and stock market data
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Seq2seq (Google) - a general-purpose encoder-decoder framework for Tensorflow
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Fairseq (Facebook) - FAIR Sequence-to-Sequence Toolkit (PyTorch)
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TensorKart - self-driving MarioKart with TensorFlow
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TensorForce - a TensorFlow library for applied RL
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Tensorlayer - a deep learning and RL library based on TensorFlow
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OpenAI Baselines - high-quality implementations of reinforcement learning algorithms
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Gym - a toolkit for developing and comparing RL algorithms
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SerpentAI - Game Agent Framework. Helping you create AIs / Bots to play any game you own
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StarGAN - PyTorch implementation of StarGAN: Unified Generative Adversarial Networks for Multi-Domain Image-to-Image Translation. StarGAN can flexibly translate an input image to any desired target domain using only a single generator and a discriminator.
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GANs with Keras - Combine multiple models into a single Keras model. GANs made easy!
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Deep Conv GANs with Keras - Keras implementation of Deep Convolutional Generative Adversarial Networks
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Anago - bidirectional LSTM-CRF for Sequence Labeling. Easy-to-use and state-of-the-art performance.
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NER with LSTM - Named Entity Recognition using multi-layered bidirectional LSTMs and task adapted word embeddings
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NeuroNER - Named-entity recognition using neural networks.
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End to end negotiator - End-to-End Learning for Negotiation Dialogues with PyTorch
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ParlAI - a framework for training and evaluating AI models on a variety of openly available dialog datasets
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Reading Wikipedia to Answer Open-Domain Questions - PyTorch implementation of the DrQA system described in the ACL 2017 paper Reading Wikipedia to Answer Open-Domain Questions.
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Text Classification - all kinds of text classificaiton models and more with deep learning
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NLP with PyTorch - IPython Notebook tutorial on deep learning for NLP, including structure prediction.
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Neural storyteller - RNN for generating little stories about images
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Generating Reviews and Discovering Sentiment - code for Learning to Generate Reviews and Discovering Sentiment
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Pattern - data mining and NLP
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spaCy - library for advanced NLP
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sense2vec - use spaCy to go beyond vanilla word2vec
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TextBlob - NLP library
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Gensim - topic modelling
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GloVe - GloVe model for learning word representations
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Newspaper - news, full-text, and article metadata extraction
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SpeakEasy-AI - project that aims to detect patterns in conversational responses.
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Rasa NLU - primarily used to build chatbots and voice apps, where this is called intent classification and entity extraction
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ChatterBot - conversational dialog engine for creating chat bots using ML
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W.I.L.L - a python written personal assistant
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Pytorch Vision - datasets, transforms and models specific to Computer Vision
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Darknet - neural network framework written in C and CUDA. It is fast, easy to install, and supports CPU and GPU computation.
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Darkflow - Translate darknet to tensorflow. Load trained weights, retrain/fine-tune using tensorflow, export constant graph def to mobile devices
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YAD2K - 90% Keras/10% Tensorflow implementation of YOLO_v2
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YOLO - Real-Time Object Detection
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RetinaNet with Keras - Keras implementation of RetinaNet object detection.
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Faster R-CNN - Towards Real-Time Object Detection with Region Proposal Networks
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Mask R-CNN - Object detection and instance segmentation on Keras and TensorFlow
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Vehicle detection - Vehicle detection using machine learning and computer vision techniques for Udacity's self-driving car course.
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CapsNet with Keras - A Keras implementation of CapsNet in NIPS2017 paper "Dynamic Routing Between Capsules". Now test error ＝ 0.34%.
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Facenet - face recognition using Tensorflow
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Face classification with Keras - real-time face detection and emotion/gender classification using fer2013/imdb datasets with a keras CNN model and openCV
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Fast Style Transfer in TensorFlow - TensorFlow CNN for fast style transfer
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Deepcolor - Automatic coloring and shading of manga-style lineart, using Tensorflow + cGANs
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DeepSpeech - TensorFlow implementation of Baidu's DeepSpeech architecture
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WaveNet with TensorFlow - TensorFlow implementation of the WaveNet generative neural network architecture for audio generation
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Speech-to-Text-WaveNet - End-to-end sentence level English speech recognition based on DeepMind's WaveNet and tensorflow
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CommAI-env - platform for developing AI systems as described in A Roadmap towards Machine Intelligence
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Universe - a software platform for measuring and training an AI's general intelligence across the world's supply of games, websites and other applications
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Universe starter agent - a starter agent that can solve a number of universe environments
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Distributed evolution (alternative to RL) - starter code for Evolution Strategies
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General AI challenge, Round1 - environment and tasks for the first round of the General AI Challenge.
- Pyro - deep probabilistic programming library built on PyTorch
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Keras convnet visualization - interactive convnet features visualization for Keras
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Perceptron - UI to test different networks
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Picasso - A CNN model visualizer
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Fabrik - collaboratively build, visualize, and design neural nets in browser
- Generative Adversarial Networks (GANs) - GANs explanation for beginners
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Artificial Intelligence: A Modern Approach - Stuart Russell & Peter Norvig
- Also consider browsing the list of recommended reading, divided by each chapter in "Artificial Intelligence: A Modern Approach".
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Paradigms Of Artificial Intelligence Programming: Case Studies in Common Lisp - Paradigms of AI Programming is the first text to teach advanced Common Lisp techniques in the context of building major AI systems
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Reinforcement Learning: An Introduction - This introductory textbook on reinforcement learning is targeted toward engineers and scientists in artificial intelligence, operations research, neural networks, and control systems, and we hope it will also be of interest to psychologists and neuroscientists.
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The Cambridge Handbook Of Artificial Intelligence - Written for non-specialists, it covers the discipline's foundations, major theories, and principal research areas, plus related topics such as artificial life
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The Emotion Machine: Commonsense Thinking, Artificial Intelligence, and the Future of the Human Mind - In this mind-expanding book, scientific pioneer Marvin Minsky continues his groundbreaking research, offering a fascinating new model for how our minds work
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Artificial Intelligence: A New Synthesis - Beginning with elementary reactive agents, Nilsson gradually increases their cognitive horsepower to illustrate the most important and lasting ideas in AI
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On Intelligence - Hawkins develops a powerful theory of how the human brain works, explaining why computers are not intelligent and how, based on this new theory, we can finally build intelligent machines. Also audio version available from audible.com
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How To Create A Mind - Kurzweil discusses how the brain works, how the mind emerges, brain-computer interfaces, and the implications of vastly increasing the powers of our intelligence to address the world’s problems
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Deep Learning - Goodfellow, Bengio and Courville's introduction to a broad range of topics in deep learning, covering mathematical and conceptual background, deep learning techniques used in industry, and research perspectives.
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The Elements of Statistical Learning: Data Mining, Inference, and Prediction - Hastie and Tibshirani cover a broad range of topics, from supervised learning (prediction) to unsupervised learning including neural networks, support vector machines, classification trees and boosting---the first comprehensive treatment of this topic in any book.
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Foundations Of Computational Agents - This book is published by Cambridge University Press, 2010
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The Quest For Artificial Intelligence - This book traces the history of the subject, from the early dreams of eighteenth-century (and earlier) pioneers to the more successful work of today's AI engineers.
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Stanford CS229 - Machine Learning - This course provides a broad introduction to machine learning and statistical pattern recognition.
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Computers and Thought: A practical Introduction to Artificial Intelligence - The book covers computer simulation of human activities, such as problem solving and natural language understanding; computer vision; AI tools and techniques; an introduction to AI programming; symbolic and neural network models of cognition; the nature of mind and intelligence; and the social implications of AI and cognitive science.
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Society of Mind - Marvin Minsky's seminal work on how our mind works. Lot of Symbolic AI concepts have been derived from this basis.
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Artificial Intelligence and Molecular Biology - The current volume is an effort to bridge that range of exploration, from nucleotide to abstract concept, in contemporary AI/MB research.
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Brief Introduction To Educational Implications Of Artificial Intelligence - This book is designed to help preservice and inservice teachers learn about some of the educational implications of current uses of Artificial Intelligence as an aid to solving problems and accomplishing tasks.
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Encyclopedia: Computational intelligence - Scholarpedia is a peer-reviewed open-access encyclopedia written and maintained by scholarly experts from around the world.
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Ethical Artificial Intelligence - a book by Bill Hibbard that combines several peer reviewed papers and new material to analyze the issues of ethical artificial intelligence.
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Deep Learning. Methods And Applications Free book from Microsoft Research
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Neural Networks And Deep Learning - Neural networks and deep learning currently provide the best solutions to many problems in image recognition, speech recognition, and natural language processing. This book will teach you the core concepts behind neural networks and deep learning
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Machine Learning: A Probabilistic Perspective - This textbook offers a comprehensive and self-contained introduction to the field of machine learning, based on a unified, probabilistic approach
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Deep Learning - Yoshua Bengio, Ian Goodfellow and Aaron Courville put together this currently free (and draft version) book on deep learning. The book is kept up-to-date and covers a wide range of topics in depth (up to and including sequence-to-sequence learning).
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Deep Learning.net - Aggregation site for DL resources
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Awesome Machine Learning - Like this Github, but ML-focused
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Awesome Deep Learning Resources - Rough list of learning resources for Deep Learning
- MIT Artifical Intelligence Videos - MIT AI Course
- Intro to Artificial Intelligence - Learn the Fundamentals of AI. Course run by Peter Norvig
- EdX Artificial Intelligence - The course will introduce the basic ideas and techniques underlying the design of intelligent computer systems
- Artificial Intelligence For Robotics - This class will teach you basic methods in Artificial Intelligence, including: probabilistic inference, planning and search, localization, tracking and control, all with a focus on robotics
- Machine Learning - Basic machine learning algorithms for supervised and unsupervised learning
- Neural Networks For Machine Learning - Algorithmic and practical tricks for artifical neural networks.
- Deep Learning - An Introductory course to the world of Deep Learning.
- Stanford Statistical Learning - Introductory course on machine learning focusing on: linear and polynomial regression, logistic regression and linear discriminant analysis; cross-validation and the bootstrap, model selection and regularization methods (ridge and lasso); nonlinear models, splines and generalized additive models; tree-based methods, random forests and boosting; support-vector machines.
- Knowledge Based Artificial Intelligence - Georgia Tech's course on Artificial Intelligence focussing on Symbolic AI.
- Prolog Programming For Artificial Intelligence - This best-selling guide to Prolog and Artificial Intelligence concentrates on the art of using the basic mechanisms of Prolog to solve interesting AI problems.
- AI Algorithms, Data Structures and Idioms in Prolog, Lisp and Java - PDF here
- Python Tools for Machine Learning
- Python for Artificial Intelligence
- AI & Society
- Annals of Mathematics and Artifical Intelligence
- Applicable Algebra in Engineering, Communication and Computing
- Applied Intelligence
- Artificial Intelligence Review
- Automated Software Engineering
- Autonomous Agents and Multi-Agent Systems
- Computational and Mathematical Organization Theory
- Evolutionary Intelligence
- Intelligent Industrial Systems
- Journal of Automated Reasoning
- Journal on Data Semantics
- Journal of Intelligent Information Systems
- Minds and Machines
- Progress in Artificial Intelligence
- Artificial Intelligence
- Journal of Artificial Intelligence Research
- AI Magazine
- EXPERT—IEEE Intelligent Systems
- Computational Intelligence
- International Journal of Intelligent Systems
- Applied Artificial Intelligence
- Knowledge Engineering Review
- Journal of Experimental and Theoretical Artificial Intelligence
- Artificial Intelligence for Engineering Design, Analysis and Manufacturing
- AI Communications
- International Journal on Artificial Intelligence Tools
- Electronic Transactions on Artificial Intelligence
- IEEE Transactions Automation Science and Engineering
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Joke dataset - A dataset of 200k English plaintext jokes.
- Open Cognition Project - We're undertaking a serious effort to build a thinking machine
- AITopics - Large aggregation of AI resources
- AIResources - Directory of open source software and open access data for the AI research community
- IEEE Computational Intelligence Society
- Machine Intelligence Research Institute
- OpenAI
- Association For The Advancement of Artificial Intelligence
- Bias problem in AI
- 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.