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STATISTICS FOR MACHINE LEARNING

By: Material type: TextTextPublication details: UK PACK PUBLISHING LTD 2017Description: v, 427ISBN:
  • 978-1-78829-575-8
Subject(s): DDC classification:
  • 006.31015195/DAN
Summary: Complex statistics in Machine Learning worry a lot of developers. Knowing statistics helps you build strong Machine Learning models that are optimized for a given problem statement. This book will teach you all it takes to perform complex statistical computations required for Machine Learning. You will gain information on statistics behind supervised learning, unsupervised learning, reinforcement learning, and more. Understand the real-world examples that discuss the statistical side of Machine Learning and familiarize yourself with it. You will also design programs for performing tasks such as model, parameter fitting, regression, classification, density collection, and more.
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Holdings
Item type Current library Call number Status Notes Date due Barcode
Books Books Symbiosis Institute of Computer Studies and Research Algorithm 006.31015195/DAN (Browse shelf(Opens below)) Checked out MACHINE LEARNING - STATISTICAL METHODS, MATHEMATICAL STATISTICS - DATA PROCESSING 04/09/2025 SICSR-B-19518
Books Books Symbiosis Institute of Operation Management A2(7) 006.310 151 95/DAN (Browse shelf(Opens below)) Available SIOM-B-14528
Books Books Symbiosis Institute of Operation Management A2(7) 006.31015195/DAN (Browse shelf(Opens below)) Available SIOM-B-14529
Books Books Symbiosis Institute of Operation Management A2(7) 006.31015195/DAN (Browse shelf(Opens below)) Available SIOM-B-14530

Complex statistics in Machine Learning worry a lot of developers. Knowing statistics helps you build strong Machine Learning models that are optimized for a given problem statement. This book will teach you all it takes to perform complex statistical computations required for Machine Learning. You will gain information on statistics behind supervised learning, unsupervised learning, reinforcement learning, and more. Understand the real-world examples that discuss the statistical side of Machine Learning and familiarize yourself with it. You will also design programs for performing tasks such as model, parameter fitting, regression, classification, density collection, and more.

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