Math for Programming: Learn the Math, Write the Better Code - Tapa blanda

Kneusel, Ronald T.

 
9781718503588: Math for Programming: Learn the Math, Write the Better Code

Sinopsis

A one-stop-shop for all the math you should have learned for your programming career.

Math for Programming summarizes all the core math topics a typical professional software engineer needs to know. The book condenses the various mathematics concepts covered in an undergraduate computer science program into a single volume, providing a starting point for independent study or a refresher for those who are some years removed from the classroom.

The book first covers preliminary subjects like number representation systems, set theory, and Boolean algebra. Then it dives into the field of discrete mathematics, including functions, induction proofs, number theory, combinatorics, graphs, and trees. The book also examines essential topics in probability, statistics, linear algebra, and calculus.

Rather than confine itself to abstract theory, the book focuses on practical application and numerical methods at the level typically encountered by working developers. Hands-on code examples in Python and C also make the topics concrete. Brush up on all the math you should have learned and level-up your career today.

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Acerca del autor

Ronald T. Kneusel is a data scientist who builds deep-learning (AI) systems, as well as extensive experience with medical imaging and the development of medical devices. He earned a PhD in machine learning from the University of Colorado, Boulder, has nearly 20 years of machine learning experience in industry, and is presently pursuing deep-learning projects with L3Harris Technologies, Inc. Kneusel is also the author of Random Numbers and Computers (Springer 2018), in addition to Math for Deep Learning, Practical Deep Learning, and Strange Code—all published by No Starch Press.

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