In this chapter, we will explain why machine learning has become so popular and discuss what kinds of problems can be solved using machine learning. Then, we will show you how to build your first …

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

We will present in this chapter of our Python Machine Learning Tutorial four important metrics. These metrics are used to evaluate the results of classifications.

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.

For this book, all of the examples are tested using Python 3 and the Scikit-learn library, a Python library that implements the various types of machine learning algorithms, such as classification, regression, …

I’ve written Machine Learning with Python for Everyone for the absolute beginner to machine learning. Even more so, you may well have very little college-level mathematics in your toolbox and I’m not …

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

In this section, we will explore some essential Python concepts that are crucial for AI & ML practitioners. Before diving into AI & ML, it’s essential to have a solid understanding of Python syntax. Here are …

We briefly discuss and explain different machine learning algorithms and real-world application areas based on machine learning. We highlight several research issues and potential future directions.

This book of Python projects in machine learning tries to do just that: to equip the developers of today and tomorrow with tools they can use to better understand, evaluate, and shape machine learning to …