Introduction to machine learning with Python: a guide for data scientists
Material type:
TextPublication details: New Delhi , SPD Shroff Publishers & distributors Pvt ltd 2018Description: xii, 376 pages : illustrations ; 24 cmISBN: - 9789352134571
- 005.133 MUL-I
| Item type | Current library | Home library | Call number | Materials specified | Status | Date due | Barcode | |
|---|---|---|---|---|---|---|---|---|
| Books and Monographs | Central Library, NIT Jalandhar General Stacks | Central Library, NIT Jalandhar | 005.133 MUL-I (Browse shelf(Opens below)) | Checked out to Sheela Tiwari (FA0345) | 12.03.2026 | 99492 | ||
| Books and Monographs | Central Library, NIT Jalandhar General Stacks | Central Library, NIT Jalandhar | 005.133 MUL-I (Browse shelf(Opens below)) | Available | 99768 | |||
| Books and Monographs | Central Library, NIT Jalandhar General Stacks | Central Library, NIT Jalandhar | 005.133 MUL-I (Browse shelf(Opens below)) | Available | 100408 | |||
| Books and Monographs | Central Library, NIT Jalandhar General Stacks | Central Library, NIT Jalandhar | 005.133 MUL-I (Browse shelf(Opens below)) | Checked out to Dr Pramod Kumar (FA0316) | 31.08.2020 | 100409 | ||
| Books and Monographs | Central Library, NIT Jalandhar General Stacks | Central Library, NIT Jalandhar | 005.133 MUL-I (Browse shelf(Opens below)) | Available | 100410 | |||
| Books and Monographs | Central Library, NIT Jalandhar General Stacks | Central Library, NIT Jalandhar | 005.133 MUL-I (Browse shelf(Opens below)) | Available | 99491 |
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. You'll learn
the steps necessary to create a successful machine-learning application with Python and the scikit-learn library. Authors Andreas Müller and
Sarah Guido focus on the practical aspects of using machine learning algorithms, rather than the math behind them. Familiarity wit...