Name: Sparse Estimation With Math and Python: 100 Exercises for Building Logic (en Inglés)
Price: 46980.00 CLP
Availability: InStock
Author: Joe Suzuki
ISBN: 9789811614378

portada Sparse Estimation With Math and Python: 100 Exercises for Building Logic (en Inglés)

Formato

Libro Físico

Editorial

Springer

Autor

Joe Suzuki

Idioma

Inglés

N° páginas

246

Encuadernación

Tapa Blanda

ISBN13

9789811614378

N° edición

Sparse Estimation With Math and Python: 100 Exercises for Building Logic (en Inglés)

Joe Suzuki (Autor) · Springer · Tapa Blanda

Libro Físico

$ 46.980

$ 93.950

Ahorras: $ 46.970

50% descuento

Envío normal

Origen: Estados Unidos (Costos de importación incluídos en el precio)

Se enviará desde nuestra bodega entre el Jueves 06 de Junio y el Martes 18 de Junio.

Lo recibirás en cualquier lugar de Chile entre 1 y 3 días hábiles luego del envío.

Reseña del libro "Sparse Estimation With Math and Python: 100 Exercises for Building Logic (en Inglés)"

The most crucial ability for machine learning and data science is mathematical logic for grasping their essence rather than knowledge and experience. This textbook approaches the essence of sparse estimation by considering math problems and building Python programs. Each chapter introduces the notion of sparsity and provides procedures followed by mathematical derivations and source programs with examples of execution. To maximize readers' insights into sparsity, mathematical proofs are presented for almost all propositions, and programs are described without depending on any packages. The book is carefully organized to provide the solutions to the exercises in each chapter so that readers can solve the total of 100 exercises by simply following the contents of each chapter.This textbook is suitable for an undergraduate or graduate course consisting of about 15 lectures (90 mins each). Written in an easy-to-follow and self-contained style, this book will also be perfect material 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 one of a series of textbooks in machine learning by the same Author. Other titles are: Statistical Learning with Math and R (https: //www.springer.com/gp/book/9789811575679)Statistical Learning with Math and Pyth (https: //www.springer.com/gp/book/9789811578762)Sparse Estimation with Math and R