Sparse Estimation with Math and R: 100 Exercises for Building Logic

Mathematical logic is essential for machine learning and data science, and this textbook approaches sparse estimation by considering math problems and building R programs. It is suitable for an undergraduate or graduate course and is written in an easy-to-follow and self-contained style.

\n Format: Paperback / softback
\n Length: 234 pages
\n Publication date: 05 August 2021
\n Publisher: Springer Verlag, Singapore
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The most crucial ability for machine learning and data science is mathematical logic, which enables a deeper understanding of their essence rather than relying solely on knowledge and experience. This textbook takes a unique approach to sparse estimation by focusing on math problems and developing R programs to illustrate key concepts. Each chapter introduces the notion of sparsity and provides step-by-step procedures, along with mathematical derivations and source programs with examples of execution. To enhance readers' insights into sparsity, mathematical proofs are presented for almost all propositions, and programs are described without relying on any packages. The book is meticulously organized to provide clear solutions to the exercises in each chapter, allowing readers to solve a total of 100 exercises by following the contents of each chapter.

This textbook is designed for an undergraduate or graduate course that spans approximately 15 lectures (each lasting 90 minutes). Written in a clear and self-contained style, it is also an excellent resource for independent learning by data scientists, machine learning engineers, and researchers interested in linear regression, generalized linear lasso, group lasso, fused lasso, graphical models, matrix decomposition, and multivariate analysis.

This book is part of a series of textbooks on machine learning authored by the same author. Other titles in the series include:

- Statistical Learning with Math and R (https://www.springer.com/gp/book/9789811575679)
- Statistical Learning with Math and Python (https://www.springer.com/gp/book/9789811578762)
- Sparse Estimation with Math and Python

\n Weight: 384g\n
Dimension: 156 x 233 x 18 (mm)\n
ISBN-13: 9789811614453\n
Edition number: 1st ed. 2021\n