Applied Machine Learning with Python
When a developer applies machine learning in the real world, he needs how machine learning projects are conducted from soup to nuts, from the moment data have to be prepared for machine learning projects, up to the possibilities presented by deep learning libraries. Selections of machine learning algorithms are usually presented in beginners books, but then the context in which they are being used tends to be missing. This book is meant as a follow-up to introductory books on machine learning, and it will fill gaps like the preparation of machine learning data for ML projects, the variety and strengths of machine learning libraries, and how projects using neural networks and deep learning algorithms are actually executed. In other words, this book embeds what has been learned in theory and in small projects, in the real-world.
|Date Of Publication||3 Dec 2020|