The Shape of Data: Geometry-Based Machine Learning and Data an*lysis in R - Marjane Mall - Image 1
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The Shape of Data: Geometry-Based Machine Learning and Data an*lysis in R

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Marque : GENERIC
Vendu par HEAVENBOOKS.MA

This advanced machine learning book highlights many algorithms from a geometric perspective and introduces tools in network science, metric geometry, and topological data an*lysis 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 introduc...

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Description produit
Marque
GENERIC
Titre principal
The Shape of Data: Geometry-Based Machine Learning and Data an*lysis in R
Editeur
No Starch Press
Type de produit
Paperback
Présentation du livre
Paperback
Release date
9/12/2023 12:00:00 AM
Langue d'origine
English
ISBN
1718503083
Dimensions
7.06 x 0.6 x 9.25 inches
Nombre de pages de livre
264 pages
Langue - Librairie
English
Résumé
This advanced machine learning book highlights many algorithms from a geometric perspective and introduces tools in network science, metric geometry, and topological data an*lysis 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 an*lysis.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 an*lysisThe way distance metrics and dimensionality reduction impact machine learningHow to visualize, embed, and an*lyze survey and text data with topology-based algorithmsNew approaches to computational solutions, including distributed computing and quantum algorithms Read more
Auteur(s)
Colleen M. Farrelly, Yaé Ulrich Gaba
Date de parution
9/12/2023 12:00:00 AM