Deep learning from scratch: building with Python from first principles (Record no. 820)

MARC details
000 -LEADER
fixed length control field 02065nam a22002177a 4500
005 - DATE AND TIME OF LATEST TRANSACTION
control field 20210129124948.0
008 - FIXED-LENGTH DATA ELEMENTS--GENERAL INFORMATION
fixed length control field 210129b ||||| |||| 00| 0 eng d
020 ## - INTERNATIONAL STANDARD BOOK NUMBER
International Standard Book Number 9789352139026
082 ## - DEWEY DECIMAL CLASSIFICATION NUMBER
Classification number 006.32
Item number WEI
100 ## - MAIN ENTRY--PERSONAL NAME
Personal name Weidman, Seth
245 ## - TITLE STATEMENT
Title Deep learning from scratch: building with Python from first principles
260 ## - PUBLICATION, DISTRIBUTION, ETC. (IMPRINT)
Name of publisher, distributor, etc. O'Reilly Media
Place of publication, distribution, etc. Sebastopol
Date of publication, distribution, etc. 2019
300 ## - PHYSICAL DESCRIPTION
Extent xiv, 235 p.
365 ## - TRADE PRICE
Price type code INR
Price amount 925.00
520 ## - SUMMARY, ETC.
Summary, etc. Description<br/><br/>All Indian Reprints of O'Reilly are printed in Grayscale<br/>With the resurgence of neural networks in the 2010s, deep learning has become essential for machine learning practitioners and even many software engineers. This book provides a comprehensive introduction for data scientists and software engineers with machine learning experience. You’ll start with deep learning basics and move quickly to the details of important advanced architectures, implementing everything from scratch along the way.Author Seth Weidman shows you how neural networks work using a first principles approach. You’ll learn how to apply multilayer neural networks, convolutional neural networks, and recurrent neural networks from the ground up. With a thorough understanding of how neural networks work mathematically, computationally, and conceptually, you’ll be set up for success on all future deep learning projects.<br/><br/>This book provides:<br/><br/>• Extremely clear and thorough mental models—accompanied by working code examples and mathematical explanations—for understanding neural networks<br/>• Methods for implementing multilayer neural networks from scratch, using an easy-to-understand object-oriented framework<br/>• Working implementations and clear-cut explanations of convolutional and recurrent neural networks<br/>• Implementation of these neural network concepts using the popular PyTorch framework
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 Python (Computer program language)
650 ## - SUBJECT ADDED ENTRY--TOPICAL TERM
Topical term or geographic name as entry element Neural networks (Computer science)
650 ## - SUBJECT ADDED ENTRY--TOPICAL TERM
Topical term or geographic name as entry element Artificial intelligence
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 Checked out Date last seen Date checked out Copy number Cost, replacement price Price effective from Koha item type
    Dewey Decimal Classification     IT & Decisions Sciences IN29488 28-01-2021 Indian Institute of Management LRC Indian Institute of Management LRC General Stacks 01/29/2021 Overseas Press India Private 692.82 2 006.32 WEI 001084 10/24/2021 07/26/2021 07/26/2021 1 925.00 01/29/2021 Book

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