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The Shape of Data: Geometry-Based Machine Learning and Data Analysis in R converted Colleen M. Farrelly

  • SKU: BELL-52356598
The Shape of Data: Geometry-Based Machine Learning and Data Analysis in R converted Colleen M. Farrelly
$ 31.00 $ 45.00 (-31%)

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The Shape of Data: Geometry-Based Machine Learning and Data Analysis in R converted Colleen M. Farrelly instant download after payment.

Publisher: No Starch Press
File Extension: PDF
File size: 7.75 MB
Pages: 264
Author: Colleen M. Farrelly, Yaé Ulrich Gaba
ISBN: 9781718503083, 1718503083
Language: English
Year: 2023
Edition: converted

Product desciption

The Shape of Data: Geometry-Based Machine Learning and Data Analysis in R converted Colleen M. Farrelly by Colleen M. Farrelly, Yaé Ulrich Gaba 9781718503083, 1718503083 instant download after payment.

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 analysis
  • The way distance metrics and dimensionality reduction impact machine learning
  • How to visualize, embed, and analyze survey and text data with topology-based algorithms
  • New approaches to computational solutions, including distributed computing and quantum algorithms

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