Sources.md

Machine Learning

• A Course in Machine Learning (PDF)
• A First Encounter with Machine Learning (PDF)
• AI Algorithms, Data Structures, and Idioms in Prolog, Lisp, and Java - George F. Luger, William A Stubblefield
• An Introduction to Statistical Learning - Gareth James, Daniela Witten, Trevor Hastie and Robert Tibshirani
• Artificial Intelligence | Machine Learning - Andrew Ng (Notes, lectures, and problems)
• [Machine Learning | Standford] (https://see.stanford.edu/Course/CS229) - Andrew Ng (Notes, lectures and videos)
• Artificial Intelligence A Modern Approach (PDF)
• Bayesian Reasoning and Machine Learning
• Computer Vision: Algorithms and Applications
• Gaussian Processes for Machine Learning
• Inductive Logic Programming
• Information Theory, Inference, and Learning Algorithms
• Introduction to Machine Learning - Alex Smola and S.V.N. Vishwanathan (PDF)
• Introduction to Machine Learning - Amnon Shashua
• Learning Deep Architectures for AI (PDF)
• Machine Learning
• Machine Learning, Neural and Statistical Classification (PDF) or online version - This book is based on the EC (ESPRIT) project StatLog.
• Natural Language Processing with Python - Edward Loper, Ewan Klein, and Steven Bird (PDF)
• Neural Networks and Deep Learning
• Probabilistic Models in the Study of Language (Draft, with R code)
• Programming Computer Vision with Python - Jan Erik Solem
• Reinforcement Learning: An Introduction
• The Elements of Statistical Learning - Trevor Hastie, Robert Tibshirani, and Jerome Friedman
• The LION Way: Machine Learning plus Intelligent Optimization
• The Python Game Book
• Naive Bayes Classifier

Websites

• Kaggle: The Home of Data Science
• UCI Machine Learning Repository
• Welcome to Deep Learning
• Excellent Answer by Franck-Dernoncourt
• Machine Learning Demos
• AI WEBSITES THAT DESIGN THEMSELVES
• A Visual Introduction to Machine Learning
• Machine Learning in Games
• Data Mining, Analytics, Big Data, and Data Science
• Reinforcement Learning
• Deep Beat(Lyrics Generating AI)
• UCI KDD Archive
• DELVE datasets
• AWS Public datasets
• Pew Research Center
• Image Databases

Libraries

Python:

• Scikit-learn:
• PyBrain
• Natural Language Toolkit(nltk)
• Theano
• Caffe(Deep learning framework by the BVLC)
• Pylearn2
• MDP (Modular toolkit for Data Processing):
• TensorFlow™
• Spark
• Milk
• OpenCV(object detection stuff)
• Machine Learning Python
• LIBSVM -- A Library for Support Vector Machines
• Keras
• Lassage (Built over Theano)
• PyTorch

Algorithms

• Kernel Density Estimation and Non-parametric Bayes Classifier
• K-Means
• Kernel Principal Components Analysis
• Linear Regression
• Neighbors (Nearest, Farthest, Range, k, Classification)
• Non-Negative Matrix Factorization
• Support Vector Machines
• Dimensionality Reduction
• Fast Singular Value Decomposition
• Decision Tree
• Bootstrapped SVM

Popular DataSets

• Titanic Dataset
• Iris Dataset
• Wine Quality Dataset
• House Prices Dataset
• Car Evaluation Data Set

Relevant Research Papers

Will be updated soon!

Podcasts

• Talking Machines
• Data Skeptic