Building Machine Learning Powered Applications

This book delves into the practical aspects of building machine learning-powered applications, focusing on the process rather than the theory.

It guides readers through the steps of developing an ML product, from initial idea to deployment and maintenance.

The book emphasizes an experimental mindset, encouraging iterative development and quick feedback loops.

It also covers common pitfalls and strategies for overcoming them, offering valuable insights for both experienced and aspiring ML practitioners.

The book provides practical advice and real-world examples to help readers build successful ML applications.