Téléchargez le livre : Dimensionality Reduction in Data Science

Dimensionality Reduction in Data Science



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Éditeur :

Springer


Paru le : 2022-07-28



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Description


This book provides a practical and fairly comprehensive review of Data Science through the lens of dimensionality reduction, as well as hands-on techniques to tackle problems with data collected in the real world. State-of-the-art results and solutions from statistics, computer science and mathematics are explained from the point of view of a practitioner in any domain science, such as biology, cyber security, chemistry, sports science and many others. Quantitative and qualitative assessment methods are described to implement and validate the solutions back in the real world where the problems originated.


The ability to generate, gather and store volumes of data in the order of tera- and exo bytes daily has far outpaced our ability to derive useful information with available computational resources for many domains.


This book focuses on data science and problem definition, data cleansing, feature selection and extraction,statistical, geometric, information-theoretic, biomolecular and machine learning methods for dimensionality reduction of big datasets and problem solving, as well as a comparative assessment of solutions in a real-world setting.


This book targets professionals working within related fields with an undergraduate degree in any science area, particularly quantitative. Readers should be able to follow examples in this book that introduce each method or technique. These motivating examples are followed by precise definitions of the technical concepts required and presentation of the results in general situations. These concepts require a degree of abstraction that can be followed by re-interpreting concepts like in the original example(s). Finally, each section closes with solutions to the original problem(s) afforded by these techniques, perhaps in various ways to compare and contrast dis/advantages to other solutions.
Pages
265 pages
Collection
n.c
Parution
2022-07-28
Marque
Springer
EAN papier
9783031053702
EAN PDF
9783031053719
Informations sur l'ebook
Nombre pages copiables
2
Nombre pages imprimables
26
Taille du fichier
4280 Ko
Ce livre est accessible aux handicaps Voir les informations sur l'accessibilité
Prix
49,57 €
EAN EPUB
9783031053719
Informations sur l'ebook
Nombre pages copiables
2
Nombre pages imprimables
26
Taille du fichier
9411 Ko
Ce livre est accessible aux handicaps Voir les informations sur l'accessibilité
Prix
49,57 €

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