| 000 -LEADER |
|---|
| fixed length control field |
nam a22 7a 4500 |
| 003 - CONTROL NUMBER IDENTIFIER |
|---|
| control field |
OSt |
| 005 - DATE AND TIME OF LATEST TRANSACTION |
|---|
| control field |
20230912145743.0 |
| 008 - FIXED-LENGTH DATA ELEMENTS--GENERAL INFORMATION |
|---|
| fixed length control field |
230912b xxu||||| |||| 00| 0 eng d |
| 020 ## - INTERNATIONAL STANDARD BOOK NUMBER |
|---|
| International Standard Book Number |
9789393330345 |
| 040 ## - CATALOGING SOURCE |
|---|
| Transcribing agency |
AEF |
| 082 ## - DEWEY DECIMAL CLASSIFICATION NUMBER |
|---|
| Edition number |
23rd ed |
| Classification number |
006.3 |
| Item number |
ARO |
| 100 ## - MAIN ENTRY--PERSONAL NAME |
|---|
| Personal name |
Arora, S. |
| 9 (RLIN) |
282 |
| 245 ## - TITLE STATEMENT |
|---|
| Title |
Data science and analytics with python |
| 250 ## - EDITION STATEMENT |
|---|
| Edition statement |
1st ed. |
| 260 ## - PUBLICATION, DISTRIBUTION, ETC. |
|---|
| Place of publication, distribution, etc. |
Hydrabad: |
| Name of publisher, distributor, etc. |
Universities press, |
| Date of publication, distribution, etc. |
2023 |
| 300 ## - PHYSICAL DESCRIPTION |
|---|
| Extent |
488 p.: |
| Dimensions |
24 cm |
| 501 ## - WITH NOTE |
|---|
| With note |
<br/>Data Science and Machine Learning are the leading buzzwords of today.<br/>This book covers all aspects of these subjects, from data definition and categorization, classification techniques, clustering and ML algorithms to data stream and association rule mining, language data processing and neural networks. It explains descriptive and inferential statistical analysis, probability distribution and density functions as well as time series. It also describes the fundamentals of Python programming, the Python environment and libraries such as scikit-learn, NumPy and pandas, and takes a deep dive into data visualization modules and tools.<br/>Mastery of these areas will enable students to become proficient and effective data scientists.<br/>Salient features<br/><br/> Ideal for undergraduate courses on Data Science and Analytics<br/> Provides step-by-step instructions for setting up the Python environment and executing various libraries and packages<br/> All chapters include relevant case studies, their Python code and output; the last chapter is dedicated to case studies<br/> Over 300 exercise questions comprising MCQs, programming exercises and concept-based questions, with answers provided for quick reference<br/> Bibliography at the end of every chapter for further reading<br/> Android app with chapter-wise PowerPoint slides and job interview questions<br/><br/>Chapter-wise PowerPoint slides are available at: www.universitiespress.com/DataScienceandAnalyticswithPython<br/> |
| 650 ## - SUBJECT ADDED ENTRY--TOPICAL TERM |
|---|
| Topical term or geographic name entry element |
Data science |
| 9 (RLIN) |
3232 |
| 650 ## - SUBJECT ADDED ENTRY--TOPICAL TERM |
|---|
| Topical term or geographic name entry element |
Programming language_Python |
| 9 (RLIN) |
3233 |
| 700 ## - ADDED ENTRY--PERSONAL NAME |
|---|
| Personal name |
Malik, L. |
| 9 (RLIN) |
3234 |
| 942 ## - ADDED ENTRY ELEMENTS (KOHA) |
|---|
| Source of classification or shelving scheme |
|
| Koha item type |
Book |
