Other Content¶
Books, blogs, courses and more forked from josephmisiti’s awesome machine learning
Blogs¶
Data Science¶
- https://jeremykun.com/
- http://iamtrask.github.io/
- http://blog.explainmydata.com/
- http://andrewgelman.com/
- http://simplystatistics.org/
- http://www.evanmiller.org/
- http://jakevdp.github.io/
- http://blog.yhat.com/
- http://wesmckinney.com
- http://www.overkillanalytics.net/
- http://newton.cx/~peter/
- http://mbakker7.github.io/exploratory_computing_with_python/
- https://sebastianraschka.com/blog/index.html
- http://camdavidsonpilon.github.io/Probabilistic-Programming-and-Bayesian-Methods-for-Hackers/
- http://colah.github.io/
- http://www.thomasdimson.com/
- http://blog.smellthedata.com/
- https://sebastianraschka.com/
- http://dogdogfish.com/
- http://www.johnmyleswhite.com/
- http://drewconway.com/zia/
- http://bugra.github.io/
- http://opendata.cern.ch/
- https://alexanderetz.com/
- http://www.sumsar.net/
- https://www.countbayesie.com
- http://blog.kaggle.com/
- http://www.danvk.org/
- http://hunch.net/
- http://www.randalolson.com/blog/
- https://www.johndcook.com/blog/r_language_for_programmers/
- http://www.dataschool.io/
Books¶
Machine learning¶
- Real World Machine Learning [Free Chapters]
- An Introduction To Statistical Learning - Book + R Code
- Elements of Statistical Learning - Book
- Probabilistic Programming & Bayesian Methods for Hackers - Book + IPython Notebooks
- Think Bayes - Book + Python Code
- Information Theory, Inference, and Learning Algorithms
- Gaussian Processes for Machine Learning
- Data Intensive Text Processing w/ MapReduce
- Reinforcement Learning: - An Introduction
- Mining Massive Datasets
- A First Encounter with Machine Learning
- Pattern Recognition and Machine Learning
- Machine Learning & Bayesian Reasoning
- Introduction to Machine Learning - Alex Smola and S.V.N. Vishwanathan
- A Probabilistic Theory of Pattern Recognition
- Introduction to Information Retrieval
- Forecasting: principles and practice
- Practical Artificial Intelligence Programming in Java
- Introduction to Machine Learning - Amnon Shashua
- Reinforcement Learning
- Machine Learning
- A Quest for AI
- Introduction to Applied Bayesian Statistics and Estimation for Social Scientists - Scott M. Lynch
- Bayesian Modeling, Inference and Prediction
- A Course in Machine Learning
- Machine Learning, Neural and Statistical Classification
- Bayesian Reasoning and Machine Learning Book+MatlabToolBox
- R Programming for Data Science
- Data Mining - Practical Machine Learning Tools and Techniques Book
Probability & Statistics¶
- Think Stats - Book + Python Code
- From Algorithms to Z-Scores - Book
- The Art of R Programming
- Introduction to statistical thought
- Basic Probability Theory
- Introduction to probability - By Dartmouth College
- Principle of Uncertainty
- Probability & Statistics Cookbook
- Advanced Data Analysis From An Elementary Point of View
- Introduction to Probability - Book and course by MIT
- The Elements of Statistical Learning: Data Mining, Inference, and Prediction. -Book
- An Introduction to Statistical Learning with Applications in R - Book
- Learning Statistics Using R
- Introduction to Probability and Statistics Using R - Book
- Advanced R Programming - Book
- Practical Regression and Anova using R - Book
- R practicals - Book
- The R Inferno - Book
Courses¶
- CS231n, Convolutional Neural Networks for Visual Recognition, Stanford University
- CS224d, Deep Learning for Natural Language Processing, Stanford University
- Oxford Deep NLP 2017, Deep Learning for Natural Language Processing, University of Oxford
- Artificial Intelligence (Columbia University) - free
- Machine Learning (Columbia University) - free
- Machine Learning (Stanford University) - free
- Neural Networks for Machine Learning (University of Toronto) - free
- Machine Learning Specialization (University of Washington) - Courses: Machine Learning Foundations: A Case Study Approach, Machine Learning: Regression, Machine Learning: Classification, Machine Learning: Clustering & Retrieval, Machine Learning: Recommender Systems & Dimensionality Reduction,Machine Learning Capstone: An Intelligent Application with Deep Learning; free
- Machine Learning Course (2014-15 session) (by Nando de Freitas, University of Oxford) - Lecture slides and video recordings.
- Learning from Data (by Yaser S. Abu-Mostafa, Caltech) - Lecture videos available