Monetizing Machine Learning by Manuel Amunategui and Mehdi Roopaei is a very interesting book in the machine learning practical applications arena.
In my view the book is a good match for:
- engineers that want to create and rapidly deploy machine learning applications served as web applications,
- Students of applied data science
- Entrepreneurs trying to prototyping an application and rise capital
- Technical and product managers
The distinct pros for reading this book are numerous:
- The reader can acquire a variety of practical skills to develop applications beyond data science
- Through consuming the content the reader can also understand the nuances of data preparation
- The reader will learn practical criteria to select the proper algorithm
- The reader will be exposed to the end to end applications design, therefore acquiring an overview on the process end to end and potentially a product view point as well.
- The book can be useful to design education material for both technical practitioners and the more technical managers.
Areas that may have been curated better:
- As most of practical, receipt like, books the book can be at times difficult to follow and to read organically if you are not planning on coding and want to get an overview on practical use cases.
- More information around the business drivers of the use cases described would be preferable for the technical manager reader.