Fundamentals of Deep Learning: (Record no. 98124)

MARC details
000 -LEADER
fixed length control field 01926 a2200217 4500
008 - FIXED-LENGTH DATA ELEMENTS--GENERAL INFORMATION
fixed length control field 231122b |||||||| |||| 00| 0 eng d
020 ## - INTERNATIONAL STANDARD BOOK NUMBER
International Standard Book Number 9789355420121
082 ## - DEWEY DECIMAL CLASSIFICATION NUMBER
Classification number 005.74015
Cutter BUD
100 ## - MAIN ENTRY--PERSONAL NAME
Personal name Buduma, Nithin
245 ## - TITLE STATEMENT
Title Fundamentals of Deep Learning:
Remainder of title Designing Next-Generation Machine Intelligence Algorithms
250 ## - EDITION STATEMENT
Edition statement 2nd Edition
260 ## - PUBLICATION, DISTRIBUTION, ETC. (IMPRINT)
Name of publisher, distributor, etc Shroff Publishers & Distributors Pvt. Ltd.
Date of publication, distribution, etc 2022
Place of publication, distribution, etc Mumbai
300 ## - PHYSICAL DESCRIPTION
Extent 392 p.
520 ## - Remark
Summary, etc We're in the midst of an AI research explosion. Deep learning has unlocked superhuman perception to power our push toward creating self-driving vehicles, defeating human experts at a variety of difficult games including Go, and even generating essays with shockingly coherent prose. But deciphering these breakthroughs often takes a PhD in machine learning and mathematics.<br/><br/>The updated second edition of this book describes the intuition behind these innovations without jargon or complexity. Python-proficient programmers, software engineering professionals, and computer science majors will be able to reimplement these breakthroughs on their own and reason about them with a level of sophistication that rivals some of the best developers in the field.<br/><br/>Learn the mathematics behind machine learning jargon<br/>Examine the foundations of machine learning and neural networks<br/>Manage problems that arise as you begin to make networks deeper<br/>Build neural networks that analyze complex images<br/>Perform effective dimensionality reduction using autoencoders<br/>Dive deep into sequence analysis to examine language<br/>Explore methods in interpreting complex machine learning models<br/>Gain theoretical and practical knowledge on generative modeling<br/>Understand the fundamentals of reinforcement learning
650 ## - SUBJECT ADDED ENTRY--TOPICAL TERM
Topical term or geographic name as entry element Deep learning
650 ## - SUBJECT ADDED ENTRY--TOPICAL TERM
Topical term or geographic name as entry element machine learning
700 ## - ADDED ENTRY--PERSONAL NAME
Personal name Buduma, Nikhil
700 ## - ADDED ENTRY--PERSONAL NAME
Personal name Papa, Joe
906 ## - LOCAL DATA ELEMENT F, LDF (RLIN)
a Business Analytics
942 ## - ADDED ENTRY ELEMENTS (KOHA)
Item type Book
Source of classification or shelving scheme Dewey Decimal Classification
Holdings
Withdrawn status Lost status Source of classification or shelving scheme Damaged status Not for loan Home library Current library Shelving location Date acquired Source of acquisition Cost, normal purchase price Programme Full call number Barcode Date last seen Date last borrowed Cost, replacement price Koha item type
    Dewey Decimal Classification     Main Library Main Library Analytics 29/11/2023 6038 1320.00   005.74015 BUD 119071 30/03/2024 21/03/2024 1650.00 Book

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