- Before Machine Learning Volume 2 - Calculus for A.I: The fundamental mathematics for Data Science and Artificial Intelligence

Having always struggled in my youth I was now motivated to find some way to grasp deeper math concepts. This book does a great job making difficult concepts much easier to understand, in the same way his other book in Algebra does as well. This series has to be one of the all-time best series in math or science I have ever read!!

I recommend this book to people brushing up on their calculus skills. It is structured clearly and the examples are clear as well. I found the examples using bees engaging and now have more respect for bees as well! Thanks for the book! I appreciate the addition of the exercises as well.

This really teaches you, before you even know it. Written perfect, right on target. If you just started, read these books first then go on buy others. Thank you.

This is not an ebook, it's just a pdf. If that's not bad enough, it has very small print, so it's impossible to read on any device.

The book thoroughly explores calculus fundamentals, making it a valuable resource for understanding the mathematical backbone of machine learning. However, it leans more towards theory than practical application, which might be a slight drawback for readers seeking direct, hands-on relevance to AI projects. Nevertheless, this book is a commendable choice for anyone looking to build a solid theoretical foundation in calculus for AI. Four stars.

"Before Machine Learning Volume 2 - Calculus for A.I" is a revelation! The author ingeniously intertwines the intricate world of calculus with the ordered elegance of bee biology. Navigating through derivatives and algorithms, the book transforms abstract concepts into a lively narrative. This isn't your typical textbook; it's a captivating dialogue that demystifies calculus. The parallels drawn between bees' disciplined behaviors and mathematical principles provide a fresh perspective. With engaging exercises and real-world applications, this journey into calculus becomes not just educational but truly enjoyable. Prepare to be enlightened and entertained as bees guide you through the mathematical realms of machine learning.

Writing about mathematics is difficult to do but Jorge does a remarkable job making it all make sense. This book is a good grounding in what this whole, so called, 'AI thing' is all about.

Calculus has never been my cup of tea but this author did a really good job of keeping me entertained by making math more intriguing and fun. Utilizing the relationship between math and bees was really interesting. It made for a great read!

Great Book with non technical way of explaining the technical concepts in a fun and enjoying manner Eager to get his other books in the series

This is an excellent book to dip into the mathematics of Machine Learning (ML). What I found great about it, is the fact that it goes straight to the point, explaining in depth topics that one actually needs when doing ML. The explanations are clear and concise. I'm glad a book like this exists, because in the big ocean that is ML, one needs distilled knowledge on what topics one needs and how they're used in the field. I recommend this book for either beginners or as a refresher for ML practitioners. The author did a great job, and I think the world needs more books like this.

I had read volume 1 of this series and yesterday I purchased this 2nd volume for my new Kindle Colorsoft. However, I am not able to open it at all on the new Kindle. I tried removing the downloaded version from my Kindle and download it again, disconnect then reconnect my wi-fi, but nothing seems to work! The attached error message keeps showing up every time. Does someone know how to fix this problem?

Muy buen libro para comprender las bases del cálculo que antecede y se ocupa en el Machine Learning.

Even If you already know calculus I think you will get something valuable from reading this. Helps to put calculus into a Machine Learning perspective and I got some golden nuggets every now and then.