Approaching (Almost) Any Machine Learning Problem

This book is designed for those with a basic understanding of machine learning and deep learning, focusing on applied aspects rather than theoretical explanations.

It covers a wide range of topics, including supervised and unsupervised learning, cross-validation, feature engineering, and model serving, with extensive Python code examples.