The Shape of Data

Geometry-Based Machine Learning and Data Analysis in R

Colleen M. Farrelly, Yae Ulrich Gaba (Autoren)

Buch | Softcover

264 Seiten

2023
No Starch Press,US (Verlag)
978-1-7185-0308-3 (ISBN)

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The Shape of Data shows how to use geometry- and topology-based algorithms for machine learning. Focused on practical applications rather than dense mathematical concepts, the book progresses through coding examples using social network data, text data, medical data, and education data. Readers will come away with an entirely new toolkit to use in their own machine-learning work, as well as with a solid understanding of some of the most exciting algorithms being used in the field today.

Colleen M. Farrelly is a senior data scientist whose academic and industry research has focused on topological data analysis, quantum machine learning, geometry-based machine learning, network science, hierarchical modeling, and natural language processing. Since graduating from the University of Miami with an MS in biostatistics, Colleen has worked as a data scientist in a vari- ety of industries, including healthcare, consumer packaged goods, biotech, nuclear engineering, marketing, and education. Colleen often speaks at tech conferences, including PyData, SAS Global, WiDS, Data Science Africa, and DataScience SALON. When not working, Colleen can be found writing haibun/haiga or swimming. Yaé Ulrich Gaba completed his doctoral studies at the University of Cape Town (UCT, South Africa) with a specialization in topology and is currently a research associate at Quantum Leap Africa (QLA, Rwanda). His research interests are computational geometry, applied algebraic topology (topologi- cal data analysis), and geometric machine learning (graph and point-cloud representation learning). His current focus lies in geometric methods in data analysis, and his work seeks to develop effective and theoretically justified algorithms for data and shape analysis using geometric and topological ideas and methods.

Erscheinungsdatum	28.08.2023
Verlagsort	San Francisco
Sprache	englisch
Maße	177 x 234 mm
Themenwelt	Informatik ► Theorie / Studium ► Künstliche Intelligenz / Robotik
	Mathematik / Informatik ► Mathematik ► Computerprogramme / Computeralgebra
	Mathematik / Informatik ► Mathematik ► Geometrie / Topologie
	Technik
ISBN-10	1-7185-0308-3 / 1718503083
ISBN-13	978-1-7185-0308-3 / 9781718503083
Zustand	Neuware