Reference material#
Relevant companion materials#
There are a lot of good materials created by Andreas Müller, one of the core developers of scikit-learn:
Book: Introduction to Machine Learning with Python: A Guide for Data Scientists
Companion Jupyter notebooks for the book available online here
Python resources#
Mike’s resources:
Programming in Python for Data Science: a set of interactive pandas/Python lessons created by Mike and two colleagues. Of particular relevance: Modules 1, 2, 4, 8.
Hands-on tutorials:
Python cheat sheet:
Numpy notes:
Courses:
Visualization#
Fundamentals of Data Visualization: General principles of visualization independent of programming language.
Online courses#
Introduction to Machine Learning by Key Capabilities for Data Science program
Machine Learning (Andrew Ng’s famous Coursera course)
Foundations of Machine Learning online course from Bloomberg.
Machine Learning Exercises In Python, Part 1 (translation of Andrew Ng’s course to Python)
Short posts/articles#
Lists of resources#
Awesome Deep Learning is a list of deep learning resources.
Misc#
Machine Learning 101 slide deck