ApproachingAny Machine Learning Problem

This practical guide to applied machine learning is for those who already have some theoretical knowledge and want to learn how to approach machine learning and deep learning problems. The book includes a lot of code and is best enjoyed with a laptop or workstation. It covers topics such as setting up a working environment, feature selection, and hyperparameter optimization. The book does not explain algorithms but is oriented towards solving problems. Subscribe to the author's YouTube channel for tutorials and ask questions on the github repo.