Machine learning using R: (Record no. 3881)

MARC details
000 -LEADER
fixed length control field 01846nam a22002297a 4500
005 - DATE AND TIME OF LATEST TRANSACTION
control field 20221220120553.0
008 - FIXED-LENGTH DATA ELEMENTS--GENERAL INFORMATION
fixed length control field 221122b ||||| |||| 00| 0 eng d
020 ## - INTERNATIONAL STANDARD BOOK NUMBER
International Standard Book Number 9781484247624
082 ## - DEWEY DECIMAL CLASSIFICATION NUMBER
Classification number 006.31
Item number RAM
100 ## - MAIN ENTRY--PERSONAL NAME
Personal name Ramasubramanian, Karthik
245 ## - TITLE STATEMENT
Title Machine learning using R:
Remainder of title with time series and industry-based use cases in R
250 ## - EDITION STATEMENT
Edition statement 2nd
260 ## - PUBLICATION, DISTRIBUTION, ETC. (IMPRINT)
Name of publisher, distributor, etc. ApressĀ 
Place of publication, distribution, etc. New York
Date of publication, distribution, etc. 2021
300 ## - PHYSICAL DESCRIPTION
Extent xxiv, 700 p.
365 ## - TRADE PRICE
Price type code INR
Price amount 1999.00
520 ## - SUMMARY, ETC.
Summary, etc. About this book<br/>Examine the latest technological advancements in building a scalable machine learning model with Big Data using R. This book shows you how to work with a machine learning algorithm and use it to build a ML model from raw data.<br/><br/>All practical demonstrations will be explored in R, a powerful programming language and software environment for statistical computing and graphics. The various packages and methods available in R will be used to explain the topics. For every machine learning algorithm covered in this book, a 3-D approach of theory, case-study and practice will be given. And where appropriate, the mathematics will be explained through visualization in R. All the images are available in color and hi-res as part of the code download.<br/><br/>This new paradigm of teaching machine learning will bring about a radical change in perception for many of those who think this subject is difficult to learn. Though theory sometimes looks difficult, especially when there is heavy mathematics involved, the seamless flow from the theoretical aspects to example-driven learning provided in this book makes it easy for someone to connect the dots.
650 ## - SUBJECT ADDED ENTRY--TOPICAL TERM
Topical term or geographic name as entry element Machine learning
650 ## - SUBJECT ADDED ENTRY--TOPICAL TERM
Topical term or geographic name as entry element R (Computer program language)
650 ## - SUBJECT ADDED ENTRY--TOPICAL TERM
Topical term or geographic name as entry element Artificial intelligence
650 ## - SUBJECT ADDED ENTRY--TOPICAL TERM
Topical term or geographic name as entry element Information visualization
942 ## - ADDED ENTRY ELEMENTS (KOHA)
Source of classification or shelving scheme Dewey Decimal Classification
Koha item type Book
Holdings
Withdrawn status Lost status Source of classification or shelving scheme Damaged status Not for loan Collection code Bill No Bill Date Home library Current library Shelving location Date acquired Source of acquisition Cost, normal purchase price Total Checkouts Full call number Accession Number Date last seen Date checked out Copy number Cost, replacement price Price effective from Koha item type
    Dewey Decimal Classification     IT & Decisions Sciences TB1974 28-10-2022 Indian Institute of Management LRC Indian Institute of Management LRC General Stacks 11/22/2022 Technical Bureau India Pvt. Ltd. 1399.30 1 006.31 RAM 003721 04/06/2023 03/21/2023 1 1999.00 11/22/2022 Book

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