Currently reading articles under label: Machine Learning

Machine Learning ML Books

Favoured

MLAPP (Kevin Murphy), Machine Learning - A Probablistic Perspective, is more comprehensive, insightful and interesting, and contains more "real" examples/problems. However, the presents are kinda out of order, which can be difficult to follow for a first book.

Machine Learning - Basics

See also: ML books.

This blog collects some useful materials for beginners.

Book: python-machine-learning-book

code on github

ML from scratch (py)

code on github

7 Types of Regression Techniques you should know (modern regressions)

analyticsvidhya

evernote backup

DMML Tools Trend & Relationship 2016

This is a summary of KD-nuggets blogs: here and here. Pictures are modified for my own notes.

Tools Associations

sunny's conclusion

Possible framework 1: Hadoop + Spark + Python + scikit.

Possible ......