Statistical Modeling in Machine Learning

Concepts and Applications

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Éditeur :

Academic Press


Paru le : 2022-10-29



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Description

Statistical Modeling in Machine Learning: Concepts and Applications presents the basic concepts and roles of statistics, exploratory data analysis and machine learning. The various aspects of Machine Learning are discussed along with basics of statistics. Concepts are presented with simple examples and graphical representation for better understanding of techniques. This book takes a holistic approach – putting key concepts together with an in-depth treatise on multi-disciplinary applications of machine learning. New case studies and research problem statements are discussed, which will help researchers in their application areas based on the concepts of statistics and machine learning.
Statistical Modeling in Machine Learning: Concepts and Applications will help statisticians, machine learning practitioners and programmers solving various tasks such as classification, regression, clustering, forecasting, recommending and more. Provides a comprehensive overview of the state-of-the-art in statistical concepts applied to Machine Learning with the help of real-life problems, applications and tutorials Presents a step-by-step approach from fundamentals to advanced techniques Includes Case Studies with both successful and unsuccessful applications of Machine Learning to understand challenges in its implementation, along with worked examples

Elsevier Science & Technology
Pages
396 pages
Collection
n.c
Parution
2022-10-29
Marque
Academic Press
EAN papier
9780323917766
EAN PDF
9780323972529

Informations sur l'ebook
Nombre pages copiables
39
Nombre pages imprimables
39
Taille du fichier
10107 Ko
Prix
187,25 €
EAN EPUB SANS DRM
9780323972529

Prix
187,25 €

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