Practical Discrete Mathematics: Discover math principles that fuel algorithms for computer science and machine learning with Python

I am a 40+ year old software guy, when i ordered it i did it because it said "practical" :) i was still afraid it would just be a book of x's & y's & fancy notations akin to hieroglyphics better suited to CS grads :)Boy was it a surprise.A fantastic perspective on how all the x's & y's have practical use & was just superb.Even though i do own a few CS & algo books this gave me a different insight to stuff i already knew.Kudo to the authors.Superb.

Very clearly written with interesting examples. Python codes work.

An engaging and edifying book, to be sure, but a "gotcha" to be aware of for the Kindle edition (or at least in my Kindle copy): super-scripts representing exponentials are entirely absent! A number like "63" is represented just like that whether it's supposed to simply be 63 or 6^3, and this flaw is very consistent throughout. In a book riddled with mathematical equations, it took me a bit of time to figure out why sometimes his math was so far off, even senseless! Then I began to check if at such times his values were actually exponentials, and it made sense. Still a very good book, but hard to imagine why they couldn't have been more careful about super-scripting where needed. Surprising in a book on ... mathematics!

This book covers the basics of discrete mathematics which opens avenues to broader computing projects. As an initiate in the study of computer science, I always believed that the mathematics of the "continuous element" was the most interesting part of engineering analysis. Apart from the necessary introduction to the notions of discrete probability, elementary theory of counting, the theory of graphs, and other additional topics, I did not give it the importance that it had. And this book showed me how wrong I was, because it is a special book for those who decide to learn the discipline in a self-taught way.The way of explaining the topics is very clear, concise, rigorous. In particular, combinatorial analysis and graph theory are presented in a way that satisfies the awake reader. The entire book is presented as separate units and is very enjoyable for anyone who wants to take this discipline seriously. It is an excellent introduction to the subject, a preamble to further studies of algorithms and computation.

As a non CS student, I have been looking for a good book that gives me a good introduction into discrete math and data structures. I haven't found any that I really liked or one that thoroughly explains stuff for me to understand, until I came across this book. Most of the books I previously came across had a lot of math and were not very intuitive. I love this book, because it does not only explain things in a way that someone not familiar with the topic would understand, but it also goes further to give some examples on how to actually apply things. I found the examples particularly helpful, especially with the fact that they are written in python. DEFINITELY RECOMMEND!!!

Disclaimer: The publisher asked me if I would review the book.This is a good book in regards to thinking in a mathematical away about ML & AI. Practically, there is a lot of mathematical and programming work to do in regards to ML & AI. For Computer Scientists: it is a nice introduction to continuous spaces and algorithms on those spaces. For the mathematically inclined: it is a nice introduction on how to pragmatically apply math to in-demand ML.I myself have a math-physics degree and have been an ML Engineer the last few years. This is a great book reconciling CS/Math perspectives.

To read and understand this book you will not need to have a Master's in Discrete mathematics. A nascent reader could start from set theory and build the knowledge base in formal logic and constructing mathematical proofs. The second part of the book gives a practical walk-through of real world implementation of Discrete mathematics in computer science. The authors used example codes written in Python which was very helpful and easy to follow.This is a very practical and useful book for someone looking to either get started in data science or expand their knowledge base and get hands on practice in data science.

I’m a few chapters in, and the content is good. But as another review mentions, superscript formatting doesn’t show on kindle. This makes parts of it incredibly confusing. For example, the following “trivial” explanation of a base 10 number, ends up feeling not so trivial:3214 = 3 ∙ 103 + 2 ∙ 102 + 1 ∙ 101 + 4 ∙ 100