MARC details
| 000 -LEADER |
|---|
| fixed length control field |
02629nam a22002777a 4500 |
| 003 - CONTROL NUMBER IDENTIFIER |
|---|
| control field |
IIITD |
| 005 - DATE AND TIME OF LATEST TRANSACTION |
|---|
| control field |
20240805132928.0 |
| 008 - FIXED-LENGTH DATA ELEMENTS--GENERAL INFORMATION |
|---|
| fixed length control field |
240725b |||||||| |||| 00| 0 eng d |
| 020 ## - INTERNATIONAL STANDARD BOOK NUMBER |
|---|
| International Standard Book Number |
9781138315068 |
| 040 ## - CATALOGING SOURCE |
|---|
| Original cataloging agency |
IIITD |
| 082 00 - DEWEY DECIMAL CLASSIFICATION NUMBER |
|---|
| Classification number |
006.3 |
| Item number |
ROG-A |
| 100 1# - MAIN ENTRY--PERSONAL NAME |
|---|
| Personal name |
Rogel-Salazar, Jesus |
| 245 10 - TITLE STATEMENT |
|---|
| Title |
Advanced data science and analytics with python |
| Statement of responsibility, etc |
by Jesus Rogel-Salazar |
| 260 ## - PUBLICATION, DISTRIBUTION, ETC. (IMPRINT) |
|---|
| Place of publication, distribution, etc |
Oxon : |
| Name of publisher, distributor, etc |
CRC Press, |
| Date of publication, distribution, etc |
©2020. |
| 300 ## - PHYSICAL DESCRIPTION |
|---|
| Extent |
xxxv, 383 p. : |
| Other physical details |
ill. ; |
| Dimensions |
25 cm. |
| 490 ## - SERIES STATEMENT |
|---|
| Series statement |
Chapman & Hall/CRC data mining & knowledge discovery series |
| 504 ## - BIBLIOGRAPHY, ETC. NOTE |
|---|
| Bibliography, etc |
Includes bibliographical references and index. |
| 505 ## - FORMATTED CONTENTS NOTE |
|---|
| Title |
1. Time Series<br/> |
| -- |
2. Speaking Naturally: Text and Natural Language Processing |
| -- |
3. Getting Social: Graph Theory and Social Network Analysis |
| -- |
4. Thinking Deeply: Neural Networks and Deep Learning |
| -- |
5. Here Is One I Made Earlier: Machine Learning Deployment |
| 520 ## - SUMMARY, ETC. |
|---|
| Summary, etc |
"Advanced Data Science and Analytics with Python enables data scientists to continue developing their skills and apply them in business as well as academic settings. The subjects discussed in this book are complementary and a follow up from the topics discuss in Data Science and Analytics with Python. The aim is to cover important advanced areas in data science using tools developed in Python such as SciKit-learn, Pandas, Numpy, Beautiful Soup, NLTK, NetworkX and others. The model development is supported by the use of frameworks such as Keras, TensorFlow and Core ML, as well as Swift for the development of iOS and MacOS applications. The book can be read independently from the previous volume and each of the chapters in this volume is sufficiently independent from the others providing flexibility for the reader. Each of the topics addressed in the book tackles the data science workflow from a practical perspective, concentrating on the process and results obtained. The implementation and deployment of trained models are central to the book. Time series analysis, natural language processing, topic modelling, social network analysis, neural networks and deep learning are comprehensively covered in the book. The book discusses the need to develop data products and tackles the subject of bringing models to their intended audiences. In this case literally to the users's fingertips in the form of an iPhone app"-- |
| 650 #0 - SUBJECT ADDED ENTRY--TOPICAL TERM |
|---|
| Topical term or geographic name as entry element |
Data mining. |
| 650 #0 - SUBJECT ADDED ENTRY--TOPICAL TERM |
|---|
| Topical term or geographic name as entry element |
Python |
| 650 #0 - SUBJECT ADDED ENTRY--TOPICAL TERM |
|---|
| Topical term or geographic name as entry element |
Databases. |
| 906 ## - LOCAL DATA ELEMENT F, LDF (RLIN) |
|---|
| a |
7 |
| b |
cbc |
| c |
orignew |
| d |
1 |
| e |
ecip |
| f |
20 |
| g |
y-gencatlg |
| 942 ## - ADDED ENTRY ELEMENTS (KOHA) |
|---|
| Source of classification or shelving scheme |
Dewey Decimal Classification |
| Koha item type |
Books |
