Math for Programmers

To land a position in fields like data science, machine learning, computer graphics, and cryptography, possessing robust mathematical abilities is crucial. "Math for Programmers" is a book that equips you with the essential math skills needed in these highly sought-after professions, with a focus tailored to developers. Enriched with an abundance of engaging graphics and over 200 exercises and mini-projects, the book opens doors to stimulating and profitable careers in today’s most exciting programming areas. Key takeaways include 2D and 3D vector math, matrices, linear transformations, core concepts from linear algebra, multivariable calculus, and algorithms for regression, classification, and clustering. It contains practical real-world examples. The book targets programmers with basic algebra knowledge, even those who might need a refresher. A formal background in linear algebra or calculus isn’t necessary. In today’s competitive landscape, companies increasingly recognize the necessity to apply data science and leverage effective machine learning strategies to stay ahead. This requires developers who are adept at coding and familiar with statistical tools, linear algebra, and calculus. Moreover, mathematics is essential in modern applications such as game development, computer graphics and animation, image and signal processing, pricing engines, and stock market analysis. Paul Orland, CEO of Tachyus, a startup in Silicon Valley, specializes in predictive analytics software aimed at optimizing energy production for the oil and gas industry. As the founding CTO, he directed the engineering team in transitioning hybrid machine learning and physics models into products, developing distributed optimization algorithms, and crafting bespoke web-based data visualizations. He holds a B.S. in mathematics from Yale University and an M.S. in physics from the University of Washington.