Review: Machine Learning Yearning

Machine Learning Yearning by Andrew Ng
My rating: 3 of 5 stars

This can be a good book to always have on the desk, why? It lists down most of the quick diagnosing things in one place, so we can look at it in the moment of confusion. If you're an ML practitioner it doesn't tell anything that is new related to algorithms or anything like that but it helps one structure his/her ml project in a coherent manner. And small bite sized chapters, much like his lectures help us to search exactly for the problem we are facing and take an action that gives the best returns.

This book will help one brush his/her thoughts in planning properly for a project and give better project completion estimates, since we have to include for things like time for error analysis, time to reclassify misclassified data etc.

I wish the scope of the book was more with respect to deep learning, like for example in the chapter titled learning from curves a great deal of important things like loss vs epoch logs have been not discussed.

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