Name: The Shape of Data: Geometry-Based Machine Learning and Data Analysis in R (en Inglés)
Price: 37.94 USD
Availability: InStock
Author: Farrelly, Colleen M. ; Ulrich Gaba, Yaé
ISBN: 9781718503083

portada The Shape of Data: Geometry-Based Machine Learning and Data Analysis in R (en Inglés)

The Shape of Data: Geometry-Based Machine Learning and Data Analysis in R (en Inglés)

Formato

Libro Físico

Autor

Colleen M. Farrelly

Yaé Ulrich Gaba

Editorial

No Starch Press

Idioma

Inglés

N° páginas

264

Encuadernación

Tapa Blanda

Dimensiones

23.2 x 17.8 x 1.2 cm

Peso

0.50 kg.

ISBN13

9781718503083

Categorías

Topología
Software de matemáticas y estadísticas
Aprendizaje automático («machine learning»)

The Shape of Data: Geometry-Based Machine Learning and Data Analysis in R (en Inglés)

Colleen M. Farrelly (Autor) · Yaé Ulrich Gaba (Autor) · No Starch Press · Tapa Blanda

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Reseña del libro "The Shape of Data: Geometry-Based Machine Learning and Data Analysis in R (en Inglés)"

This advanced machine learning book highlights many algorithms from a geometric perspective and introduces tools in network science, metric geometry, and topological data analysis through practical application. Whether you're a mathematician, seasoned data scientist, or marketing professional, you'll find The Shape of Data to be the perfect introduction to the critical interplay between the geometry of data structures and machine learning. This book's extensive collection of case studies (drawn from medicine, education, sociology, linguistics, and more) and gentle explanations of the math behind dozens of algorithms provide a comprehensive yet accessible look at how geometry shapes the algorithms that drive data analysis. In addition to gaining a deeper understanding of how to implement geometry-based algorithms with code, you'll explore: Supervised and unsupervised learning algorithms and their application to network data analysisThe way distance metrics and dimensionality reduction impact machine learningHow to visualize, embed, and analyze survey and text data with topology-based algorithmsNew approaches to computational solutions, including distributed computing and quantum algorithms