A Summary of each chapter of the book "Machine Learning Engineering in Action" by Ben Wilson.
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This book covers the road map of ML projects on a high level. It focuses on recommendations and tips to ensure the project reaches production. The author adopts a different approach that highlights how not to do things and what to avoid through examples of common mistakes in the industry.
This book is destined to anyone that is involved with the making of ML projects with wide spectrum of technical skills.
This book does not propose any models or algorithms that work best or compare them. It overpasses these technical aspects.
The summaries will be added and updated as I'm reading the book.