Machine learning concepts with Python and the Jupyter Notebook environment : using Tensorflow 2.0 (Record no. 297466)
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| 000 -LEADER | |
|---|---|
| fixed length control field | 02341nam a22001817a 4500 |
| 020 ## - INTERNATIONAL STANDARD BOOK NUMBER | |
| International Standard Book Number | 9781484267387 |
| 082 ## - DEWEY DECIMAL CLASSIFICATION NUMBER | |
| Classification number | 006.31 |
| Item number | SIL-M |
| 100 ## - MAIN ENTRY--PERSONAL NAME | |
| Personal name | Silaparasetty, Nikita |
| 245 ## - TITLE STATEMENT | |
| Title | Machine learning concepts with Python and the Jupyter Notebook environment : using Tensorflow 2.0 |
| Statement of responsibility, etc. | By Nikita Silaparasetty. |
| 260 ## - PUBLICATION, DISTRIBUTION, ETC. | |
| Place of publication, distribution, etc. | [Berkeley, CA] : |
| Name of publisher, distributor, etc. | Apress, |
| Date of publication, distribution, etc. | c2020. |
| 300 ## - PHYSICAL DESCRIPTION | |
| Extent | i-xxvii+290P. |
| 500 ## - GENERAL NOTE | |
| General note | First south Asian Edition published in 2021. |
| 504 ## - BIBLIOGRAPHY, ETC. NOTE | |
| Bibliography, etc. note | Includes index. |
| 505 ## - FORMATTED CONTENTS NOTE | |
| Formatted contents note | Chapter 1: An Overview of Artificial Intelligence --<br/>Chapter 2: An Overview of Machine Learning --<br/>Chapter 3: Introduction to Deep Learning --<br/>Chapter 4: Machine Learning Versus Deep Learning --<br/>Chapter 5: Machine Learning with Python --<br/>Chapter 6: Introduction to Jupyter Notebooks --<br/>Chapter 7: Python Programming on the Jupyter Notebook --<br/>Chapter 8: The Tensorflow Machine Learning Library --<br/>Chapter 9: Programming with Tensorflow 1.0 --<br/>Chapter 10: Introducing TensorFlow 2.0 --<br/>Chapter 11: Machine Learning Programming with TensorFlow 2.0. |
| 520 ## - SUMMARY, ETC. | |
| Summary, etc. | Create, execute, modify, and share machine learning applications with Python in the Jupyter Notebook environment. This book breaks down any barriers to programming machine learning applications through the use of Jupyter Notebooks instead of a text editor or a regular IDE. Youll start by learning fundamental concepts in Python necessary for working with machine learning application development. Then use Jupyter Notebooks to improve the way you program with Python. After grounding your skills in working with Python in Jupyter Notebooks, youll dive into what TensorFlow is, how it helps machine learning enthusiasts, and how to tackle the challenges it presents. Along the way, sample programs created using Jupyter Notebooks allow you to apply concepts from earlier in the book. Those who are new to machine learning can start in with these easy programs and develop basic skills. A glossary at the end of the book provides common machine learning and Python keywords and definitions to make learning even easier. You will: Program machine learning models in Python Tackle basic machine learning obstacles Develop in the Jupyter Notebooks environment. |
| 650 ## - SUBJECT ADDED ENTRY--TOPICAL TERM | |
| Topical term or geographic name entry element | TensorFlow. Machine learning. Python (Computer program language) |
| 942 ## - ADDED ENTRY ELEMENTS (KOHA) | |
| Koha item type | Book |
| Withdrawn status | Lost status | Damaged status | Not for loan | Home library | Current library | Shelving location | Date acquired | Total Checkouts | Full call number | Barcode | Date last seen | Date last checked out | Price effective from | Koha item type |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| Dept. of Computational Biology and Bioinformatics | Dept. of Computational Biology and Bioinformatics | Processing Center | 22/10/2021 | 3 | 006.31 SIL-M | DCB3983 | 31/03/2023 | 28/10/2022 | 22/10/2021 | Book | ||||
| Dept. of Linguistics | Dept. of Linguistics | Processing Center | 12/11/2021 | 3 | 006.31 SIL | LIN10630 | 19/07/2022 | 14/07/2022 | 12/11/2021 | Book |