Learn how the Adadelta optimization algorithm really works by coding it from the ground up in Python. Perfect for ML enthusiasts who want to go beyond the black box!

Overview Beginner-friendly books simplify Python, R, statistics, and machine learning concepts.Practical examples and projects make data science easier to under ...

As a Python library for machine learning, with deliberately limited scope, Scikit-learn is very good. It has a wide assortment of well-established algorithms, with integrated graphics.

IBM’s Uncertainty Qualification 360 is an open source library of Python algorithms for quantifying, estimating, and communicating the uncertainty of machine learning models.

It covers basic algorithm design techniques such as divide and conquer, dynamic programming, and greedy algorithms. It concludes with a brief introduction to intractability (NP-completeness) .