Introduction

Welcome to Machine Learning Engineering, a compendium of notable concepts for developing and understanding the engineering and technical foundations that power machine learning solutions.

This resource is not centered on the mathematical or statistical foundations of Artificial Intelligence. Instead, it highlights on the engineering and computer science aspects crucial for developing and creating effective machine learning systems.

Who This Resource Is For

This collection assumes prior knowledge of Machine Learning principles. Familiarity with programming languages used in ML, the ML/DL ecosystem, foundational concepts that power these models and an understanding of how Machine Learning addresses business challenges are essential for effectively engaging with and contributing to the content of this resource.

Those who are passionate about developer experience and appreciate the sophistication of tools and software that make ML accessible to organizations will find the content engaging. The goal is to foster a broader vision for creating elegant solutions that others can collaborate on, leveraging the right tools to tackle interesting engineering challenges.

Note: This material provides concise examples, ideas, and implementations rather than exhaustive definitions or in-depth explanations. It references external sources for core concepts, allowing you to revisit them later if needed.