After finishing the book, the author encourages readers to share it with friends and teammates so that more people on the team can apply the same machine learning strategy ideas.

Google

Machine learning is a highly iterative process. When building a machine learning system, the author often follows a loop: start with an idea about how to build the system, implement the idea in code, and carry out an experiment that tells how well the idea worked. Based on what is learned, generate more ideas and keep iterating; many dozens of ideas may be tried before finding one that is satisfactory.

Iterative Loop of Machine Learning Development

Machine Learning Yearning, a free ebook from Andrew Ng, teaches you how to structure Machine Learning projects.
https://www.deeplearning.ai/machine-learning-yearning/

Note: The content of the book is aligned with the Coursera Deeplearning.ai specialization.  https://www.deeplearning.ai/deep-learning-specialization/ 

Machine Learning Yearning (Deeplearning.ai)

The faster one can go around the iterative machine learning development loop, the faster one will make progress.

Faster Iteration Cycles Accelerate ML Progress

When a team has several ideas for improving a cat detector, it can efficiently evaluate those ideas in parallel.

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