Optimization for Data Analysis Stephen J. Wright and Benjamin Recht is an English-language textbook on optimization techniques in data science and data analysis. This self-contained work discusses core principles and algorithms that are essential for researchers, students, and professionals.
The book covers fundamental optimization techniques relevant to data science, such as gradient methods, stochastic gradients, coordinate descent, and methods for advanced problems with constraints and non-smooth functions. It also addresses analysis of these functions and optimization duality, as well as backpropagation for neural networks.
This practical approach connects optimization techniques with data analysis, giving readers insight into formulating and solving standard problems in data science. The book’s content aligns with optimization, linear programming, and general mathematics.