Machine Learning Infrastructure and Best Practices for Software Engineers

Preface

Machine learning has gained a lot of popularity in recent years. The introduction of large language models such as GPT-3 and 4 only increased the speed of the development of this field. These large language models have become so powerful that it is almost impossible to train them on a local computer. However, this is not necessary at all. These language models provide the ability to create new tools without the need to train them because they can be steered by the context window and the prompt.

In this book, my goal is to show how machine learning models can be trained, evaluated, and tested – both in the context of a small prototype and in the context of a fully-fledged software product. The primary objective of this book is to bridge ...