Good links to read and save for data science and machine learning.
- Statistical Learning Notes (Series)
- Machine Learning Tutorial for Beginners (Kaggle)
- eBooks Mathematics for Machine Learning by Marc Peter Deisenroth, A Aldo Faisal, and Cheng Soon Ong
- Machine Learning Crash course by Google (no certificate).
- Machine Learning by Andrew Ng on Coursera (my notes for this course)
- Machine Learning A-Z™: Hands-On Python & R In Data Science from A-Z on Udemy (my note for this course)
- Statistical Learning course by Stanford University (free, certificate, in R). One can find the python codes here or here.
- Blog Basic ML by Tiep Vu (in Vietnamese)
- Learn from ML experts at Google by Google
- Machine Learning Mastery by John Brownlee
- In-depth introduction to machine learning in 15 hours of expert videos
- (Book) Introduction to statistic learning James, Witten, Hastie and Tibshirani (with the course Statistical Learning above)
- (Book) Elements of Statistical Learning
- Your First Machine Learning Project in Python Step-By-Step
- How do artificial neural networks work? (Quora)
- scikit-learn : learn on kaggle
- Learn skills on kaggle (python, pandas, machine learning, data visualisation, sql, r, deep learning)
- Big data university, IBM cloud (expired April 6, 2019)
- The Data Science Handbook (free): This book is not for self-learning data science, it talks about data world instead. This book contains “in-depth interviews with 25 remarkable data scientists, where they share their insights, stories, and advice.”
- Data Scientist path on Dataquest. (see my notes for this path)
- Data Scientist path on OpenClassRoom (in french)
- CS109 Data Science by Harvard.
- Statistical Data Analysis in Python by Christopher Fonnesbeck.
- Probability & Statistics for Data Science (Series)
- No free hunch (Kaggle’s official blog).
Towards Data Science: medium style, many intuitive posts on statistics and data science.