Hands-on machine learning with Scikit-Learn and TensorFlow : concepts, tools, and techniques to build intelligent systems (Record no. 2668)
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| 000 -LEADER | |
|---|---|
| fixed length control field | 03740nam a22002417a 4500 |
| 003 - CONTROL NUMBER IDENTIFIER | |
| control field | OSt |
| 005 - DATE AND TIME OF LATEST TRANSACTION | |
| control field | 20231214162706.0 |
| 008 - FIXED-LENGTH DATA ELEMENTS--GENERAL INFORMATION | |
| fixed length control field | 231214b ||||| |||| 00| 0 eng d |
| 020 ## - INTERNATIONAL STANDARD BOOK NUMBER | |
| International Standard Book Number | 978-93-5542-198-2 |
| 028 ## - PUBLISHER NUMBER | |
| Source | Allied Informatics |
| Bill Number | 11447 |
| Bill Date | 08-12-2023 |
| Purchase Year | 2023 |
| 040 ## - CATALOGING SOURCE | |
| Original cataloging agency | DDC |
| Language of cataloging | English |
| Transcribing agency | 0 |
| 082 ## - DEWEY DECIMAL CLASSIFICATION NUMBER | |
| Classification number | 6.31 GER |
| 100 ## - MAIN ENTRY--PERSONAL NAME | |
| Personal name | Geron, Aurelien |
| 245 ## - TITLE STATEMENT | |
| Title | Hands-on machine learning with Scikit-Learn and TensorFlow : concepts, tools, and techniques to build intelligent systems |
| 250 ## - EDITION STATEMENT | |
| Remainder of edition statement | 3rd |
| 260 ## - PUBLICATION, DISTRIBUTION, ETC. | |
| Place of publication, distribution, etc. | Mumbai |
| Name of publisher, distributor, etc. | Shroff Publishers & Distributers Pvt Ltd. |
| Date of publication, distribution, etc. | 2022 |
| 300 ## - PHYSICAL DESCRIPTION | |
| Dimensions | 834 pg |
| 500 ## - GENERAL NOTE | |
| General note | Through a recent series of breakthroughs, deep learning has boosted the entire field of machine learning. Now, even programmers who know close to nothing about this technology can use simple, efficient tools to implement programs capable of learning from data. This best-selling book uses concrete examples, minimal theory, and production-ready Python frameworks--scikit-learn, Keras, and TensorFlow--to help you gain an intuitive understanding of the concepts and tools for building intelligent systems. With this updated third edition, author Aurelien Geron explores a range of techniques, starting with simple linear regression and progressing to deep neural networks. Numerous code examples and exercises throughout the book help you apply what you've learned. Programming experience is all you need to get started. Use scikit-learn to track an example machine learning project end to end Explore several models, including support vector machines, decision trees, random forests, and ensemble methods Exploit unsupervised learning techniques such as dimensionality reduction, clustering, and anomaly detection Dive into neural net architectures, including convolutional nets, recurrent nets, generative adversarial networks, and transformers Use TensorFlow and Keras to build and train neural nets for computer vision, natural language processing, generative models, and deep reinforcement learning Train neural nets using multiple GPUs and deploy them at scale using Google's Vertex AI |
| 520 ## - SUMMARY, ETC. | |
| Summary, etc. | Through a recent series of breakthroughs, deep learning has boosted the entire field of machine learning. Now, even programmers who know close to nothing about this technology can use simple, efficient tools to implement programs capable of learning from data. This best-selling book uses concrete examples, minimal theory, and production-ready Python frameworks--scikit-learn, Keras, and TensorFlow--to help you gain an intuitive understanding of the concepts and tools for building intelligent systems. With this updated third edition, author Aurelien Geron explores a range of techniques, starting with simple linear regression and progressing to deep neural networks. Numerous code examples and exercises throughout the book help you apply what you've learned. Programming experience is all you need to get started. Use scikit-learn to track an example machine learning project end to end Explore several models, including support vector machines, decision trees, random forests, and ensemble methods Exploit unsupervised learning techniques such as dimensionality reduction, clustering, and anomaly detection Dive into neural net architectures, including convolutional nets, recurrent nets, generative adversarial networks, and transformers Use TensorFlow and Keras to build and train neural nets for computer vision, natural language processing, generative models, and deep reinforcement learning Train neural nets using multiple GPUs and deploy them at scale using Google's Vertex AI |
| 650 ## - SUBJECT ADDED ENTRY--TOPICAL TERM | |
| Topical term or geographic name entry element | Machine learning, Computing Skill |
| 700 ## - ADDED ENTRY--PERSONAL NAME | |
| Personal name | Build Intelligent System |
| 942 ## - ADDED ENTRY ELEMENTS (KOHA) | |
| Source of classification or shelving scheme | |
| Koha item type | Reference |
| Withdrawn status | Lost status | Source of classification or shelving scheme | Damaged status | Not for loan | Collection code | Permanent Location | Current Location | Date acquired | Source of acquisition | Cost, normal purchase price | Total Checkouts | Full call number | Barcode | Date last seen | Date last checked out | Cost, replacement price | Price effective from | Koha item type |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| Reference | BSDU Knowledge Resource Center, Jaipur | BSDU Knowledge Resource Center, Jaipur | 2023-12-14 | Allied Informatics | 3000.00 | 4 | 6.31 GER | 018203 | 2024-07-08 | 2024-01-08 | 3000.00 | 2023-12-14 | Books |