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

Every great programming challenge has mathematical principles at its heart. Whether you’re optimizing search algorithms, building physics engines for games, or training neural networks, success depends on your grasp of core mathematical concepts.

In Math for Programming, you’ll master the essential mathematics that will take you from basic coding to serious software development. You’ll discover how vectors and matrices give you the power to handle complex data, how calculus drives optimization and machine learning, and how graph theory leads to advanced search algorithms.

Through clear explanations and practical examples, you’ll learn to:

Harness linear algebra to manipulate data with unprecedented efficiency
Apply calculus concepts to optimize algorithms and drive simulations
Use probability and statistics to model uncertainty and analyze data
Master the discrete mathematics that powers modern data structures
Solve dynamic problems through differential equations

Whether you’re seeking to fill gaps in your mathematical foundation or looking to refresh your understanding of core concepts, Math for Programming will turn complex math into a practical tool you’ll use every day.

About the Author

Ronald T. Kneusel has been working with machine learning in industry since 2003 and has a PhD in machine learning from the University of Colorado, Boulder. Kneusel is the author of Practical Deep Learning, Math for Deep Learning, The Art of Randomness, How AI Works, and Strange Code (all from No Starch Press), as well as Numbers and Computers and Random Numbers and Computers (Springer).

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Account dedicated to Print on Demand titles.

CANCELLATION
You can send a cancellation request from the order page while the package has not yet been shipped. After that we cannot ensure we can retrieve the parcel but we suggest you to get in touch with us in order to verify the case.

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