We focus on using Python and the scikit-learn library, and work through all the steps to create a successful machine learning application. The meth‐ods we introduce will be helpful for scientists and …

A problem with machine learning, especially when you are starting out and want to learn about the algorithms, is that it is often difficult to get suitable test data.

Repository for Machine Learning resources, frameworks, and projects. Managed by the DLSU Machine Learning Group. - MLResources/books/ [ML] Introduction to Machine Learning with Python …

Discuss machine learning using Python and the Scikit-learn libraries. Where possible, I will manually implement the relevant machine learning algorithm using Python.

Welcome to the second edition of Machine Learning Engineering with Python, a book that aims to introduce you to the exciting world of making machine learning (ML) systems production-ready.

"Machine Learning with Python" by G. R. Liu provides a comprehensive introduction to the essential concepts, theories, computational techniques, and applications of machine learning.

This machine learning course is designed for Python developers who want to learn the theory and application of a large variety of machine learning methods. Starting from simple linear regression, …

The tutorial aims to equip developers with the knowledge needed to apply Python in building scalable machine learning applications.

For those who do wish to look at the programming aspect of machine learning, Chapter 13 walks you through the entire process of setting up a supervised learning model using the popular programming …

What follows next are three Python machine learning projects. They will help you create a machine learning classifier, build a neural network to recognize handwritten digits, and give you a background …