MARC details
| 000 -LEADER |
|---|
| fixed length control field |
03531nmm a22003497a 4500 |
| 003 - CONTROL NUMBER IDENTIFIER |
|---|
| control field |
OSt |
| 005 - DATE AND TIME OF LATEST TRANSACTION |
|---|
| control field |
20240812145733.0 |
| 008 - FIXED-LENGTH DATA ELEMENTS--GENERAL INFORMATION |
|---|
| fixed length control field |
240812b |||||||| |||| 00| 0 eng d |
| 020 ## - INTERNATIONAL STANDARD BOOK NUMBER |
|---|
| International Standard Book Number |
9781837635504 (e-book) |
| 040 ## - CATALOGING SOURCE |
|---|
| Transcribing agency |
Cavite State University - Main Campus Library |
| Description conventions |
rda |
| 041 ## - LANGUAGE CODE |
|---|
| Language code of text/sound track or separate title |
eng |
| 050 ## - LIBRARY OF CONGRESS CALL NUMBER |
|---|
| Classification number |
QA280 |
| Item number |
R12 2023 |
| 100 ## - MAIN ENTRY--PERSONAL NAME |
|---|
| Personal name |
Rafferty, Greg |
| 9 (RLIN) |
28860 |
| Relator term |
author |
| 245 ## - TITLE STATEMENT |
|---|
| Title |
Forecasting time series data with Prophet : |
| Remainder of title |
build, improve, and optimize time series forecasting models using Meta's advanced forecasting tool / |
| Statement of responsibility, etc. |
by Greg Rafferty |
| 250 ## - EDITION STATEMENT |
|---|
| Edition statement |
2nd. ed. |
| 260 ## - PUBLICATION, DISTRIBUTION, ETC. |
|---|
| Place of publication, distribution, etc. |
Birmingham, UK : |
| Name of publisher, distributor, etc. |
Packt Publishing Ltd, |
| Date of publication, distribution, etc. |
2023 |
| 300 ## - PHYSICAL DESCRIPTION |
|---|
| Extent |
1 online resource (282, pages) : |
| Other physical details |
color illustrations. |
| 336 ## - CONTENT TYPE |
|---|
| Source |
rdacontent |
| Content type term |
text |
| 337 ## - MEDIA TYPE |
|---|
| Source |
rdamedia |
| Media type term |
computer |
| 338 ## - CARRIER TYPE |
|---|
| Source |
rdacarrier |
| Carrier type term |
online resource |
| 500 ## - GENERAL NOTE |
|---|
| General note |
https://portal.igpublish.com/iglibrary/ is required to read this e-book. |
| 504 ## - BIBLIOGRAPHY, ETC. NOTE |
|---|
| Bibliography, etc. note |
Includes index |
| 505 ## - FORMATTED CONTENTS NOTE |
|---|
| Formatted contents note |
Part 1. Getting started with prophet -- 1. The history and development of time series forecasting -- 2. Getting started with prophet -- 3. How prophet works -- Part 2. Seasonality, tuning, and advanced features -- 4. Handling non-daily data -- 5. Working with seasonality -- 6. Forecasting holiday effects -- 7. Controlling growth modes -- 8. Influencing trend changepoints -- 9. Including additional regressors -- 10. Accounting for outliers and special events -- <br/>11. Managing uncertainty intervals -- Part 3. Diagnostics and evaluation -- 12. Performing cross-validation -- 13. Evaluating performance metrics -- 14. Productional zing prophet |
| 520 ## - SUMMARY, ETC. |
|---|
| Summary, etc. |
Prophet enables Python and R developers to build scalable time series forecasts. This book will help you to implement Prophet's cutting-edge forecasting techniques to model future data with higher accuracy and with very few lines of code.<br/><br/>You will begin by exploring the evolution of time series forecasting, from the basic early models to the advanced models of the present day. The book will demonstrate how to install and set up Prophet on your machine and build your fi rst model with only a few lines of code. You'll then cover advanced features such as visualizing your forecasts, adding holidays, seasonality, and trend changepoints, handling outliers, and more, along with understanding why and how to modify each of the default parameters. Later chapters will show you how to optimize more complicated models with hyperparameter tuning and by adding additional regressors to the model. Finally, you'll learn how to run diagnostics to evaluate the performance of your models and see some useful features when running Prophet in production environments.<br/><br/>By the end of this Prophet book, you will be able to take a raw time series dataset and build advanced and accurate forecast models with concise, understandable, and repeatable code. |
| 541 ## - IMMEDIATE SOURCE OF ACQUISITION NOTE |
|---|
| Source of acquisition |
Fund 164 |
| Vendor |
CE-Logic |
| Method of acquisition |
Purchased |
| Date of acquisition |
February 19, 2024 |
| Accession number |
OEBP000454<br/> |
| Owner |
P. Roderno |
| Purchase price |
PHP 5,586.00 <br/> |
| PO No. |
2024-02-0124 |
| Sales Invoice No. |
2024-1-113 |
| 650 #0 - SUBJECT ADDED ENTRY--TOPICAL TERM |
|---|
| Topical term or geographic name entry element |
Time-series analysis |
| 9 (RLIN) |
2379 |
| General subdivision |
Data processing |
| 650 #0 - SUBJECT ADDED ENTRY--TOPICAL TERM |
|---|
| Topical term or geographic name entry element |
Python (Computer program language) |
| 9 (RLIN) |
4472 |
| 650 #0 - SUBJECT ADDED ENTRY--TOPICAL TERM |
|---|
| Topical term or geographic name entry element |
Machine learning |
| 9 (RLIN) |
17626 |
| 856 ## - ELECTRONIC LOCATION AND ACCESS |
|---|
| Electronic File |
<a href="https://portal.igpublish.com/iglibrary/obj/PACKT0006618?searchid=1720070661322Q2BFX9HcjrPbzU47fZ4B3">https://portal.igpublish.com/iglibrary/obj/PACKT0006618?searchid=1720070661322Q2BFX9HcjrPbzU47fZ4B3</a> |
| Link text |
Click here to read Full-Text E-Book |
| 856 ## - ELECTRONIC LOCATION AND ACCESS |
|---|
| Electronic File |
<a href="https://docs.google.com/forms/d/e/1FAIpQLSfSoAj3qM4b_ttQMZLuimqgwkfHDH1NyJ7S4eyjHD7Vr4j7EQ/viewform">https://docs.google.com/forms/d/e/1FAIpQLSfSoAj3qM4b_ttQMZLuimqgwkfHDH1NyJ7S4eyjHD7Vr4j7EQ/viewform</a> |
| Link text |
Log-in to the website is required to read this e-book. Click here to request access. |
| 942 ## - ADDED ENTRY ELEMENTS (KOHA) |
|---|
| Source of classification or shelving scheme |
Library of Congress Classification |
| Koha item type |
Online E-Books |
