Statistical Inference and Machine Learning for Big Data

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Éditeur :

Springer


Collection :

Springer Series in the Data Sciences

Paru le : 2022-11-30

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Description

This book presents a variety of advanced statistical methods at a level suitable for advanced undergraduate and graduate students as well as for others interested in familiarizing themselves with these important subjects. It proceeds to illustrate these methods in the context of real-life applications in a variety of areas such as genetics, medicine, and environmental problems.
The book begins in Part I by outlining various data types and by indicating how these are normally represented graphically and subsequently analyzed. In Part II, the basic tools in probability and statistics are introduced with special reference to symbolic data analysis. The most useful and relevant results pertinent to this book are retained. In Part III, the focus is on the tools of machine learning whereas in Part IV the computational aspects of BIG DATA are presented.
This book would serve as a handy desk reference for statistical methods at the undergraduate and graduate level as well as be useful in courses which aim to provide an overview of modern statistics and its applications.
Pages
431 pages
Collection
Springer Series in the Data Sciences
Parution
2022-11-30
Marque
Springer
EAN papier
9783031067839
EAN PDF
9783031067846

Informations sur l'ebook
Nombre pages copiables
4
Nombre pages imprimables
43
Taille du fichier
8806 Ko
Prix
147,69 €
EAN EPUB
9783031067846

Informations sur l'ebook
Nombre pages copiables
4
Nombre pages imprimables
43
Taille du fichier
44247 Ko
Prix
147,69 €