MARC details
| 000 -LEADER |
|---|
| fixed length control field |
02977nam a22003375i 4500 |
| 001 - CONTROL NUMBER |
|---|
| control field |
21744360 |
| 003 - CONTROL NUMBER IDENTIFIER |
|---|
| control field |
OSt |
| 005 - DATE AND TIME OF LATEST TRANSACTION |
|---|
| control field |
20260306144541.0 |
| 008 - FIXED-LENGTH DATA ELEMENTS--GENERAL INFORMATION |
|---|
| fixed length control field |
201005s2020 inu 000 0 eng |
| 010 ## - LIBRARY OF CONGRESS CONTROL NUMBER |
|---|
| LC control number |
2020947403 |
| 020 ## - INTERNATIONAL STANDARD BOOK NUMBER |
|---|
| International Standard Book Number |
9789363866249 |
| 035 ## - SYSTEM CONTROL NUMBER |
|---|
| System control number |
21744360 |
| 040 ## - CATALOGING SOURCE |
|---|
| Original cataloging agency |
DLC |
| Language of cataloging |
eng |
| Description conventions |
rda |
| Transcribing agency |
DLC |
| 042 ## - AUTHENTICATION CODE |
|---|
| Authentication code |
pcc |
| 082 ## - DEWEY DECIMAL CLASSIFICATION NUMBER |
|---|
| Edition number |
1 |
| Classification number |
006.31 |
| Item number |
LAZF |
| 100 1# - MAIN ENTRY--PERSONAL NAME |
|---|
| Personal name |
Lazzeri, Francesca. |
| 9 (RLIN) |
254051 |
| 245 10 - TITLE STATEMENT |
|---|
| Title |
Machine Learning : |
| Remainder of title |
for Time Series Forecasting With Python / |
| Statement of responsibility, etc. |
Francesca Lazzeri. |
| 250 ## - EDITION STATEMENT |
|---|
| Edition statement |
1st ed. |
| 263 ## - PROJECTED PUBLICATION DATE |
|---|
| Projected publication date |
2011 |
| 264 #1 - PRODUCTION, PUBLICATION, DISTRIBUTION, MANUFACTURE, AND COPYRIGHT NOTICE |
|---|
| Place of production, publication, distribution, manufacture |
New Delhi : |
| Name of producer, publisher, distributor, manufacturer |
Wiley India Pvt Ltd. |
| Date of production, publication, distribution, manufacture, or copyright notice |
2025. |
| 300 ## - PHYSICAL DESCRIPTION |
|---|
| Extent |
xxii,230 p.; |
| Other physical details |
PB |
| Dimensions |
23.5 cm. |
| 336 ## - CONTENT TYPE |
|---|
| Content type term |
text |
| Content type code |
txt |
| Source |
rdacontent |
| 337 ## - MEDIA TYPE |
|---|
| Media type term |
unmediated |
| Media type code |
n |
| Source |
rdamedia |
| 338 ## - CARRIER TYPE |
|---|
| Carrier type term |
volume |
| Carrier type code |
nc |
| Source |
rdacarrier |
| 500 ## - GENERAL NOTE |
|---|
| General note |
Machine Learning for Time Series Forecasting with Python is full real-world examples, resources, and concrete strategies to help readers explore and transform data and develop usable, practical time series forecasts. This book is perfect for entry-level data scientists, business analysts, developers, and researchers. This book offers a comprehensive introduction to the core concepts, terminology, approaches, and applications of machine learning and deep learning for time series forecasting: understanding these principles leads to more flexible and successful time series applications.<br/><br/>Apart from this, in this Indian Adaptation, you’ll get:<br/>·New self-evaluation Multiple Choice, Review, and Job-Interview Questions to equip the knowledge and confidence to excel in interviews<br/>·India-specific case studies, Time Series Forecasting for Demand Planning at Flipkart and Predictive Maintenance at Tata Steel.<br/>·Appendix on “Enhancing Time Series Forecasting for the Indian Market” |
| 505 ## - FORMATTED CONTENTS NOTE |
|---|
| Statement of responsibility |
Machine Learning for Time Series Forecasting with Python is full real-world examples, resources, and concrete strategies to help readers explore and transform data and develop usable, practical time series forecasts. This book is perfect for entry-level data scientists, business analysts, developers, and researchers. This book offers a comprehensive introduction to the core concepts, terminology, approaches, and applications of machine learning and deep learning for time series forecasting: understanding these principles leads to more flexible and successful time series applications.<br/><br/>Apart from this, in this Indian Adaptation, you’ll get:<br/>·New self-evaluation Multiple Choice, Review, and Job-Interview Questions to equip the knowledge and confidence to excel in interviews<br/>·India-specific case studies, Time Series Forecasting for Demand Planning at Flipkart and Predictive Maintenance at Tata Steel.<br/>·Appendix on “Enhancing Time Series Forecasting for the Indian Market” |
| 650 ## - SUBJECT ADDED ENTRY--TOPICAL TERM |
|---|
| Topical term or geographic name entry element |
Time series data preparation |
| 9 (RLIN) |
254085 |
| 650 ## - SUBJECT ADDED ENTRY--TOPICAL TERM |
|---|
| Source of heading or term |
Introduction to neural networks for time series forecasting |
| 942 ## - ADDED ENTRY ELEMENTS (KOHA) |
|---|
| Source of classification or shelving scheme |
Dewey Decimal Classification |
| Koha item type |
Book |
| Edition |
1 |
| Call number prefix |
006.31 LAZF |
