Deep learning with R (Record no. 2645)
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| 000 -LEADER | |
|---|---|
| fixed length control field | 01736nam a22002297a 4500 |
| 005 - DATE AND TIME OF LATEST TRANSACTION | |
| control field | 20220716110122.0 |
| 008 - FIXED-LENGTH DATA ELEMENTS--GENERAL INFORMATION | |
| fixed length control field | 220716b ||||| |||| 00| 0 eng d |
| 020 ## - INTERNATIONAL STANDARD BOOK NUMBER | |
| International Standard Book Number | 9789811358494 |
| 082 ## - DEWEY DECIMAL CLASSIFICATION NUMBER | |
| Classification number | 006.31 |
| Item number | GHA |
| 100 ## - MAIN ENTRY--PERSONAL NAME | |
| Personal name | Ghatak, Abhijit |
| 245 ## - TITLE STATEMENT | |
| Title | Deep learning with R |
| 260 ## - PUBLICATION, DISTRIBUTION, ETC. (IMPRINT) | |
| Name of publisher, distributor, etc. | Springer |
| Place of publication, distribution, etc. | Switzerland |
| Date of publication, distribution, etc. | 2019 |
| 300 ## - PHYSICAL DESCRIPTION | |
| Extent | xxiii, 245 p. |
| 365 ## - TRADE PRICE | |
| Price type code | EURO |
| Price amount | 89.99 |
| 520 ## - SUMMARY, ETC. | |
| Summary, etc. | About this book<br/>Deep Learning with R introduces deep learning and neural networks using the R programming language. The book builds on the understanding of the theoretical and mathematical constructs and enables the reader to create applications on computer vision, natural language processing and transfer learning. <br/><br/>The book starts with an introduction to machine learning and moves on to describe the basic architecture, different activation functions, forward propagation, cross-entropy loss and backward propagation of a simple neural network. It goes on to create different code segments to construct deep neural networks. It discusses in detail the initialization of network parameters, optimization techniques, and some of the common issues surrounding neural networks such as dealing with NaNs and the vanishing/exploding gradient problem. Advanced variants of multilayered perceptrons namely, convolutional neural networks and sequence models are explained, followed by application to different use cases. The book makes extensive use of the Keras and TensorFlow frameworks. <br/><br/> |
| 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 | Computer programming |
| 650 ## - SUBJECT ADDED ENTRY--TOPICAL TERM | |
| Topical term or geographic name as entry element | Computer science--Mathematics |
| 942 ## - ADDED ENTRY ELEMENTS (KOHA) | |
| Source of classification or shelving scheme | Dewey Decimal Classification |
| Koha item type | Book |
| 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 | TB842 | 30-06-2022 | Indian Institute of Management LRC | Indian Institute of Management LRC | General Stacks | 07/16/2022 | Technical Bureau India Pvt. Ltd. | 5088.48 | 1 | 006.31 GHA | 002784 | 10/10/2022 | 09/01/2022 | 1 | 7739.14 | 07/16/2022 | Book |