MARC details
000 -LEADER |
fixed length control field |
01788nam a22002177a 4500 |
003 - CONTROL NUMBER IDENTIFIER |
control field |
IIITD |
005 - DATE AND TIME OF LATEST TRANSACTION |
control field |
20240514153836.0 |
008 - FIXED-LENGTH DATA ELEMENTS--GENERAL INFORMATION |
fixed length control field |
240427b |||||||| |||| 00| 0 eng d |
020 ## - INTERNATIONAL STANDARD BOOK NUMBER |
International Standard Book Number |
9781617293702 |
040 ## - CATALOGING SOURCE |
Original cataloging agency |
IIITD |
082 ## - DEWEY DECIMAL CLASSIFICATION NUMBER |
Classification number |
006.31 |
Item number |
TRA-D |
100 ## - MAIN ENTRY--PERSONAL NAME |
Personal name |
Trask, Andrew W. |
245 ## - TITLE STATEMENT |
Title |
Grokking deep learning |
Statement of responsibility, etc |
by Andrew W. Trask. |
260 ## - PUBLICATION, DISTRIBUTION, ETC. (IMPRINT) |
Place of publication, distribution, etc |
Greenwich : |
Name of publisher, distributor, etc |
Manning, |
Date of publication, distribution, etc |
©2019 |
300 ## - PHYSICAL DESCRIPTION |
Extent |
309 p. : |
Other physical details |
ill. ; |
Dimensions |
24 cm. |
501 ## - WITH NOTE |
With note |
Including index. |
505 ## - FORMATTED CONTENTS NOTE |
Title |
Chapter 1. Introducing deep learning: why you should learn it<br/> |
-- |
Chapter 2. Fundamental concepts: how do machines learn?<br/> |
-- |
Chapter 3. Introduction to neural prediction: forward propagation |
-- |
Chapter 4. Introduction to neural learning: gradient descent |
-- |
Chapter 5. Learning multiple weights at a time: generalizing gradient descent<br/> |
-- |
Chapter 6. Building your first deep neural network: introduction to backpropagation |
-- |
Chapter 7. How to picture neural networks: in your head and on paper |
-- |
Chapter 8. Learning signal and ignoring noise: introduction to regularization and batching |
-- |
Chapter 9. Modeling probabilities and nonlinearities: activation functions<br/> |
-- |
Chapter 10. Neural learning about edges and corners: intro to convolutional neural networks<br/> |
-- |
Chapter 11. Neural networks that understand language: king – man + woman == ? |
-- |
Chapter 12. Neural networks that write like Shakespeare: recurrent layers for variable-length data |
-- |
Chapter 13. Introducing automatic optimization: let’s build a deep learning framework |
-- |
Chapter 14. Learning to write like Shakespeare: long short-term memory |
-- |
Chapter 15. Deep learning on unseen data: introducing federated learning<br/> |
-- |
Chapter 16. Where to go from here: a brief guide |
650 ## - SUBJECT ADDED ENTRY--TOPICAL TERM |
Topical term or geographic name as entry element |
neural networks |
650 ## - SUBJECT ADDED ENTRY--TOPICAL TERM |
Topical term or geographic name as entry element |
language modeling |
942 ## - ADDED ENTRY ELEMENTS (KOHA) |
Source of classification or shelving scheme |
Dewey Decimal Classification |
Koha item type |
Books |
Koha issues (borrowed), all copies |
1 |