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Building Machine
Learning Systems

Batch, Real-Time, and LLM Systems

Complementary Chapter for Free!

Overview of this book’s mission by it's author;

The goal of this book is to introduce ML systems built with feature stores, and how to build the pipelines (programs with well-defined inputs and outputs) for ML systems while following MLOps best practices for the incremental development and improvement of your ML systems.

‍In the complimentary chapter, you will:

  • ‍‍Learn how to build 3 types of ML systems in a unified architecture: Batch, Real-TIme, and LLMs.
  • Learn about real-world applications in batch, real-time and LLM machine learning systems.
Get Your Early Copy

Building Machine
Learning Systems

Batch, Real-Time, and LLM Systems

First Chapter for Free!

Overview of this book’s mission by the Author:

The goal of this book is to introduce ML systems built with feature stores, and how to build the pipelines (programs with well-defined inputs and outputs) for ML systems while following MLOps best practices for the incremental development and improvement of your ML systems.

‍In the introduction chapter, you will:

  1. ‍‍Learn how to build 3 types of ML systems in a unified architecture: Batch, Real-TIme, and LLMs.
  2. Learn about real-world applications in batch, real-time and LLM machine learning systems.
Get Your Early Copy