This is a list of free resources to learn Machine Learning. Feel free to submit your PR correcting anything you feel like and/or adding new materials that are either free or reasonable cheap, as Coursera Certifications
Data Analist Nanodegree [Udacity]
Instructors: Cheng Han-Lee, Miriam Swords Kalk
TODO: add other courses Courses:
Big Data Specialization [Coursera]
Courses:
- Introduction to Big Data
- Machine Learning with Big Data
- Graph Analytics for Big Data
- Introduction to Big Data Analytics
- Hadoop Platform and Application Framework
Courses:
- DS101x: Statistical Thinking for Data Science and Analytics
- DS102x: Machine Learning for Data Science and Analytics
- DS103x: Enabling Technologies for Data Science and Analytics: The Internet of Things
Machine Learning Specialization [Coursera]
Instructors: Emily Fox, Carlos Guestrin
Machine Learning [Coursera]
Instructors: Andrew Ng
University: Stanford
Pros/cons:
- Strong focus on algorithms and models, less on statistics
- Plenty of insightful details from teacher
- Student gets hand on experience with programming assignments using MATLAB/Octave
- Weak focus on large data sets
Original course resources: Playlist on Youtube, Website
###Intro to Machine Learning [Udacity]
Instructors: Sebastian Thrun
University: Stanford
###Introduction to Big Data [Coursera]
Instructors: Natasha Balac
Institute: San Diego Supercomputer Center (SDSC)
###Machine Learning with Big Data [Coursera]
Instructors: Paul Rodriguez, Natasha Balac
Institute: San Diego Supercomputer Center (SDSC)
###Graph Analytics for Big Data [Coursera]
Instructors: Amarnath Gupta
Institute: San Diego Supercomputer Center (SDSC)
###Introduction to Big Data Analytics [Coursera]
Instructors: Paul Rodriguez, Andrea Zonca, Natasha Balac
Institute: San Diego Supercomputer Center (SDSC)
###Hadoop Platform and Application Framework [Coursera]
Instructors: Natasha Balac, Paul Rodriguez, Andrea Zonca
Institute: San Diego Supercomputer Center (SDSC)
###DS101x: Statistical Thinking for Data Science and Analytics [edX]
Instructors:
University: Columbia University
###DS102x: Machine Learning for Data Science and Analytics [edX]
Instructors:
University: Columbia University
###DS103x: Enabling Technologies for Data Science and Analytics: The Internet of Things [edX]
Instructors:
University: Columbia University
Instructor: Mark Schmidt
University: University of British Columbia
Instructor: Mark Schmidt
University: University of British Columbia
Instructor: Nando de Freitas
University: University of Oxford
"Deep Learning" course at Oxford University. Yes, it is about Machine Learning, but anyway he is about modern approaches in the machine learning area. Website includes slides and videos.
Additional material:
Neural Networks for Machine Learning [Coursera]
Instructor: Geoffrey Hinton
University: University of Toronto
Pros/cons:
- Complex
- Covers lot of topics
- Lots of supplementary reading
Instructor: Richard Zemel
University: University of Toronto
Machine Learning [Coursera]
Instructor: Pedro Domingos
University: University of Washington
- BIG-ML Interesting blog an product
- Machine Learning Overview – Part 1 of 4
- Machine Learning Overview – Part 2 of 4 Logistic Regression
- Machine Learning Overview – Part 3 of 4 Decission Tress and random forests
- Machine Learning Overview – Part 4 of 4 Bias, Variance and Overfitting.
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Cleaning and preparing data with Python Pandas A series of tutorials on how to use python pandas, using notebooks
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Quartz/bad-data-guide bad-data-guide: An exhaustive reference to problems seen in real-world data along with suggestions on how to resolve them. Added by @avanderm
Special thanks to:
- miguelsaddress
- avanderm
- @vladyslav_chikov