Applied Machine Learning and AI for Engineers: Solve Business Problems That Can't Be Solved Algorithmically

I knew literally nothing about machine learning before reading this book - but I know basic algorithms, high school math, and Python. That was enough for me to easily follow this book and get a great start on my path towards working on ML and AI projects in the future. I give it top marks!

This is a well-produced book with all illustrations and code segments in colour. The author walks you through the exercises in each chapter, but does not explain any code. I was then obliged to read up on the code in other resources, such as ChatGPT. This is not necessarily a bad thing, as arguably I ended up with a better understanding of the code, rather than if I had simply read a description of the code in the book.

This is a great book for both people who never tried to approach AI development and for those who started but did not have a full understanding of some topics or libraries. I loved to see the problems solved with different strategies and methodologies and comparing the results. Also, the insights with the linked articles are precious to go deeper in the math which is well hidden by the python libraries. Even if the latest GPT model are not explicitly covered, this is absolutely unnecessary because once you get what's behind, you'll discover that GPT is just a more complex model base on the same concepts exposed here.

Same algorithms, same examples, same datasets. This book is just a reprint of all previous AI/Python books - nothing new. If you remove the words “for Engineers,” nothing will change. The book tries to explain some algorithms but avoids any math, which makes it hard for beginners to understand and boring for those who are already familiar with the algorithms.