Feature Engineering for Machine Learning: Principles and Techniques for Data Scientists

The description will have you believe that this book is over 600 pages, making the £48 seem justified.At just 191 pages however, this is book is a grossly overpriced. Content is good, but not worth this price!

Me ha gustado que este libro hace un repaso de múltiples técnicas para distintos tipos de datos. Me hubiera gustado más profundidad en los primeros temas pero en general cumple con lo que esperaba.

Great book. Well written. Higly recommend this for anyone who want To learn features enginnering

It's great that someone's written a book about Feature Engineering and it contains a lot of interesting material. I also like that clear readable coding examples are included (Python), so that the reader can try at home.But, it feels unfinished. The book is pretty short and the set of topics seems more like what the authors were interested in than a survey of the field. The level of explanation varies from super-detailed to glossing over concepts and technical terms that most readers won't know.The biggest issue is that the graphics are mostly hand-drawn on some kind of tablet and look like they were scrawled out quickly. I've attached one example. As you can see, they didn't even bother to adjust the contrast. So, the images have a dull gray background. Disappointing that O'Reilly didn't take care of this for the authors.

Very technical. Good book to get in and get out.