Machine Learning Engineering

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Good book

This book is an exceptional follow through on the part of the author of the 100 page machine learning book. He covers the 'engineering' of machine learning from start to finish. The 100 page machine learning book introduces the reader to machine learning algorithms and the 'math' behind the magic. However, deploying a machine learning solution is much more than the model. The author clearly outlines the principles once must understand to successfully deploy a machine learning solution.I particularly enjoyed Sections 1.4 and 1.5 when to use and when not to use machine learning. From the discussion one can clearly set forth the criteria establishing when one should pursue a machine learning solution and when one should pursue other alternatives. A brief stop in each section will undoubtedly save many both valuable time and frustration.Overall, an excellent work. If you are interested in machine learning I highly recommend this book as well as 'The 100 Page Machine Learning Book.'

Great book amazing format

The book defines the machine learning project life cycle and presents theory and strategies behind each step. Furthermore, the author presents code snippets to demonstrate the key ideas but do not expect any coding solution similar to "Hands-on Machine Learning with Scikit-Learn, Keras, and TensorFlow: Concepts, Tools, and Techniques to Build Intelligent Systems" and "Approaching (Almost) Any Machine Learning Problem" books. Similar to "The Hundred-Page Machine Learning Book" the quality of the book is great.