Introduction To Machine Learning With Python (Record no. 38172)
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| 000 -LEADER | |
|---|---|
| fixed length control field | 01894nam a22001937a 4500 |
| 020 ## - INTERNATIONAL STANDARD BOOK NUMBER | |
| ISBN | 978-9352134571 |
| 082 ## - DEWEY DECIMAL CLASSIFICATION NUMBER | |
| Classification number | 006.31 MUL |
| 100 ## - MAIN ENTRY--AUTHOR NAME | |
| Personal name | Andreas C Muller |
| 100 ## - MAIN ENTRY--AUTHOR NAME | |
| Personal name | Sarah Guido |
| 245 ## - TITLE STATEMENT | |
| Title | Introduction To Machine Learning With Python |
| 250 ## - EDITION STATEMENT | |
| Edition statement | 1 |
| 260 ## - PUBLICATION, DISTRIBUTION, ETC. (IMPRINT) | |
| Name of publisher | Shroff/O'Reilly |
| Place of publication | Navi Mumbai |
| Year of publication | 2025 |
| 300 ## - PHYSICAL DESCRIPTION | |
| Number of Pages | Print length β : β 392 pages |
| Other physical details | Item Weight β : β 600 g Dimensions β : β 18 x 1 x 24 cm |
| 520 ## - SUMMARY, ETC. | |
| Summary, etc | Machine learning has become an integral part of many commercial applications and research projects, but this field is not exclusive to large companies with extensive research teams. If you use Python, even as a beginner, this book will teach you practical ways to build your own machine learning solutions. With all the data available today, machine learning applications are limited only by your imagination.<br/><br/>You'll learn the steps necessary to create a successful machine-learning application with Python and the scikit-learn library. Authors Andreas MΕΈller and Sarah Guido focus on the practical aspects of using machine learning algorithms, rather than the math behind them. Familiarity with the NumPy and matplotlib libraries will help you get even more from this book.<br/><br/>With this book, you'll learn:<br/>Fundamental concepts and applications of machine learning<br/>Advantages and shortcomings of widely used machine learning algorithms<br/>How to represent data processed by machine learning, including which data aspects to focus on<br/>Advanced methods for model evaluation and parameter tuning<br/>The concept of pipelines for chaining models and encapsulating your workflow<br/>Methods for working with text data, including text-specific processing techniques<br/>Suggestions for improving your machine learning and data science skills. |
| 546 ## - LANGUAGE NOTE | |
| Language note | Language β : β English |
| 650 ## - SUBJECT ADDED ENTRY--TOPICAL TERM | |
| Topical Term | CSE |
| 942 ## - ADDED ENTRY ELEMENTS (KOHA) | |
| Koha item type | Text Book |
| 952 ## - LOCATION AND ITEM INFORMATION (KOHA) | |
| Damaged status | |
| Not for loan | |
| Withdrawn status | Collection code | Permanent Location | Current Location | Date acquired | Source of acquisition | Cost, normal purchase price | Inventory number | Full call number | Accession Number | Price effective from | Koha item type |
|---|---|---|---|---|---|---|---|---|---|---|---|
| Computer Science and Engineering | VAST Central Library | VAST Central Library | 10/01/2026 | Cosmo Books | 1300.00 | K797 | 006.31 MUL | 38347 | 03/02/2026 | Text Book |