Neural networks and deep learning : a textbook (Record no. 2105)
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| 000 -LEADER | |
|---|---|
| fixed length control field | 01757nam a22001697a 4500 |
| 005 - DATE AND TIME OF LATEST TRANSACTION | |
| control field | 20240229160614.0 |
| 008 - FIXED-LENGTH DATA ELEMENTS--GENERAL INFORMATION | |
| fixed length control field | 240229b |||||||| |||| 00| 0 eng d |
| 020 ## - INTERNATIONAL STANDARD BOOK NUMBER | |
| International Standard Book Number | 9783319944623 |
| 082 ## - DEWEY DECIMAL CLASSIFICATION NUMBER | |
| Classification number | 006.3 |
| Item number | AGG |
| 100 ## - MAIN ENTRY--PERSONAL NAME | |
| Personal name | Charu C. Aggarwal |
| 245 ## - TITLE STATEMENT | |
| Title | Neural networks and deep learning : a textbook |
| Remainder of title | a textbook |
| Statement of responsibility, etc. | Charu C. Aggarwal |
| 260 ## - PUBLICATION, DISTRIBUTION, ETC. | |
| Place of publication, distribution, etc. | Cham, Switzerland, |
| Name of publisher, distributor, etc. | Springer, |
| Date of publication, distribution, etc. | 2018 |
| 300 ## - PHYSICAL DESCRIPTION | |
| Page number | xxiii, 497 pages |
| Dimensions | 27 cm |
| 505 ## - FORMATTED CONTENTS NOTE | |
| Title | 1 An Introduction to Neural Networks.- 2 Machine Learning with Shallow Neural Networks.- 3 Training Deep Neural Networks.- 4 Teaching Deep Learners to Generalize.- 5 Radical Basis Function Networks.- 6 Restricted Boltzmann Machines.- 7 Recurrent Neural Networks.- 8 Convolutional Neural Networks.- 9 Deep Reinforcement Learning.- 10 Advanced Topics in Deep Learning. |
| 520 ## - SUMMARY, ETC. | |
| Summary, etc. | This book covers both classical and modern models in deep learning. The primary focus is on the theory and algorithms of deep learning. The theory and algorithms of neural networks are particularly important for understanding important concepts, so that one can understand the important design concepts of neural architectures in different applications. Why do neural networks work? When do they work better than off-the-shelf machine-learning models? When is depth useful? Why is training neural networks so hard? What are the pitfalls? The book is also rich in discussing different applications in order to give the practitioner a flavor of how neural architectures are designed for different types of problems. Applications associated with many different areas like recommender systems, machine translation, image captioning, image classification, reinforcement-learning based gaming, and text analytics are covered |
| 942 ## - ADDED ENTRY ELEMENTS (KOHA) | |
| Source of classification or shelving scheme | Dewey Decimal Classification |
| Koha item type | Books |
| 952 ## - LOCATION AND ITEM INFORMATION (KOHA) | |
| -- | 6229 |
| Withdrawn status | Lost status | Source of classification or shelving scheme | Damaged status | Not for loan | Collection code | Home library | Current library | Shelving location | Date acquired | Source of acquisition | Cost, normal purchase price | Inventory number | Total Checkouts | Full call number | Barcode | Checked out | Date last seen | Date last checked out | Cost, replacement price | Price effective from | Currency | Koha item type |
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| Dewey Decimal Classification | Non-fiction | IIITDM Kurnool | IIITDM Kurnool | General Stacks | 29.02.2024 | Bombay Books | 49.99 | 603 dt 15-01-2024 | 1 | 006.3 AGG | 0005473 | 03.05.2025 | 04.03.2024 | 04.03.2024 | 49.99 | 29.02.2024 | INR | Books |