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Thank you for purchasing the MEAP for Design a Machine Learning System (From Scratch)!

We're excited to have you join us on this journey into the world of Machine Learning Operations (MLOps). This book is designed to equip you with the knowledge and practical skills needed to build and deploy machine learning systems using open-source tools.

This book assumes you have some existing programming experience, particularly with Python, and a basic understanding of Machine Learning concepts. We'll guide you through the process of setting up a Machine Learning platform and explore the typical learning path of a Machine Learning Engineer.

The book is structured around two core projects, each tackling real-world industry use cases like image classification and recommendation systems. Through these projects, you'll gain hands-on experience with various stages of the machine learning workflow, including:

  • Orchestrating ML pipelines
  • Productionizing ML Models
  • Data Analysis & Preparation
  • Model Training & Validation
  • Model Inference & Serving
  • Monitoring & Explainability

Each chapter delves into specific machine learning steps and introduces relevant open-source tools to achieve your goals. You'll discover the diverse landscape of available tools and learn how to choose the right ones for different tasks and scenarios.

We believe that learning by doing is the most effective approach, and this book is designed to provide you with a practical and engaging learning experience.

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