introduction.md

How do you organize an AI project?

AI, Machine Learning and Deep Learning are transforming numerous industries. I have been writing a book, Machine Learning Yearning, to teach you how to structure Machine Learning projects.

This book is focused not on teaching you ML algorithms, but on how to make ML algorithms work. Some technical AI classes will give you a hammer; this book teaches you how to use the hammer. If you aspire to be a technical leader in AI and want to learn how to set direction for your team, this book will help.

After reading Machine Learning Yearning, you will be able to:​

• Prioritize the most promising directions for an AI project
• Diagnose errors in a machine learning system
• Build ML in complex settings, such as mismatched training/test sets
• Set up an ML project to compare to and/or surpass human-level performance
• Know when and how to apply end-to-end learning, transfer learning, and multi-task learning

Historically, the only way to learn how to make these "strategy" decisions has been a multi-year apprenticeship in a graduate program or company. I am writing Machine Learning Yearning to help you quickly gain this skill so that you can become better at building AI systems.

The book will be around 100 pages, and contain many easy-to-read 1-2 page chapters. If you would like to receive a draft of each chapter as it is finished, please sign up for the mailing list.

Andrew Ng