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 |
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| 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 |
