Practical Time Series Analysis: Master Time Series Data Processing, Visualization, and Modeling using Python
bStep by Step guide filled with real world practical examples./bh2About This Book/h2ulliGet your first experience with data analysis with one of the most powerful types of analysis- time-series./liliFind patterns in your data and predict the future pattern based on historical data./liliLearn the sta...
Gespeichert in:
| 1. Verfasser: | |
|---|---|
| Format: | Elektronisch E-Book |
| Sprache: | English |
| Veröffentlicht: |
Birmingham
Packt Publishing Limited
2017
|
| Ausgabe: | 1 |
| Schlagworte: | |
| Zusammenfassung: | bStep by Step guide filled with real world practical examples./bh2About This Book/h2ulliGet your first experience with data analysis with one of the most powerful types of analysis- time-series./liliFind patterns in your data and predict the future pattern based on historical data./liliLearn the statistics, theory, and implementation of Time-series methods using this example-rich guide/li/ulh2Who This Book Is For/h2This book is for anyone who wants to analyze data over time and/or frequency. A statistical background is necessary to quickly learn the analysis methods.h2What You Will Learn/h2ulliUnderstand the basic concepts of Time Series Analysis and appreciate its importance for the success of a data science project/liliDevelop an understanding of loading, exploring, and visualizing time-series data/liliExplore auto-correlation and gain knowledge of statistical techniques to deal with non-stationarity time series/liliTake advantage of exponential smoothing to tackle noise in time series data/liliLearn how to use auto-regressive models to make predictions using time-series data/liliBuild predictive models on time series using techniques based on auto-regressive moving averages/liliDiscover recent advancements in deep learning to build accurate forecasting models for time series/liliGain familiarity with the basics of Python as a powerful yet simple to write programming language/li/ulh2In Detail/h2Time Series Analysis allows us to analyze data which is generated over a period of time and has sequential interdependencies between the observations. This book describes special mathematical tricks and techniques which are geared towards exploring the internal structures of time series data and generating powerful descriptive and predictive insights. |
| Beschreibung: | 1 Online-Ressource (244 Seiten) |
| ISBN: | 9781788294195 |
Internformat
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| 520 | |a bStep by Step guide filled with real world practical examples./bh2About This Book/h2ulliGet your first experience with data analysis with one of the most powerful types of analysis- time-series./liliFind patterns in your data and predict the future pattern based on historical data./liliLearn the statistics, theory, and implementation of Time-series methods using this example-rich guide/li/ulh2Who This Book Is For/h2This book is for anyone who wants to analyze data over time and/or frequency. | ||
| 520 | |a A statistical background is necessary to quickly learn the analysis methods.h2What You Will Learn/h2ulliUnderstand the basic concepts of Time Series Analysis and appreciate its importance for the success of a data science project/liliDevelop an understanding of loading, exploring, | ||
| 520 | |a and visualizing time-series data/liliExplore auto-correlation and gain knowledge of statistical techniques to deal with non-stationarity time series/liliTake advantage of exponential smoothing to tackle noise in time series data/liliLearn how to use auto-regressive models to make predictions using time-series data/liliBuild predictive models on time series using techniques based on auto-regressive moving averages/liliDiscover recent advancements in deep learning to build accurate forecasting models for time series/liliGain familiarity with the basics of Python as a powerful yet simple to write programming language/li/ulh2In Detail/h2Time Series Analysis allows us to analyze data which is generated over a period of time and has sequential interdependencies between the observations. This book describes special mathematical tricks and techniques which are geared towards exploring the internal structures of time series data and generating powerful descriptive and predictive insights. | ||
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| id | DE-604.BV047070034 |
| illustrated | Not Illustrated |
| index_date | 2024-07-03T16:13:34Z |
| indexdate | 2024-07-10T09:01:44Z |
| institution | BVB |
| isbn | 9781788294195 |
| language | English |
| oai_aleph_id | oai:aleph.bib-bvb.de:BVB01-032477060 |
| oclc_num | 1227477905 |
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| physical | 1 Online-Ressource (244 Seiten) |
| psigel | ZDB-5-WPSE |
| publishDate | 2017 |
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| publisher | Packt Publishing Limited |
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| spelling | Pal, Dr. Avishek Verfasser aut Practical Time Series Analysis Master Time Series Data Processing, Visualization, and Modeling using Python Pal, Dr. Avishek 1 Birmingham Packt Publishing Limited 2017 1 Online-Ressource (244 Seiten) txt rdacontent c rdamedia cr rdacarrier bStep by Step guide filled with real world practical examples./bh2About This Book/h2ulliGet your first experience with data analysis with one of the most powerful types of analysis- time-series./liliFind patterns in your data and predict the future pattern based on historical data./liliLearn the statistics, theory, and implementation of Time-series methods using this example-rich guide/li/ulh2Who This Book Is For/h2This book is for anyone who wants to analyze data over time and/or frequency. A statistical background is necessary to quickly learn the analysis methods.h2What You Will Learn/h2ulliUnderstand the basic concepts of Time Series Analysis and appreciate its importance for the success of a data science project/liliDevelop an understanding of loading, exploring, and visualizing time-series data/liliExplore auto-correlation and gain knowledge of statistical techniques to deal with non-stationarity time series/liliTake advantage of exponential smoothing to tackle noise in time series data/liliLearn how to use auto-regressive models to make predictions using time-series data/liliBuild predictive models on time series using techniques based on auto-regressive moving averages/liliDiscover recent advancements in deep learning to build accurate forecasting models for time series/liliGain familiarity with the basics of Python as a powerful yet simple to write programming language/li/ulh2In Detail/h2Time Series Analysis allows us to analyze data which is generated over a period of time and has sequential interdependencies between the observations. This book describes special mathematical tricks and techniques which are geared towards exploring the internal structures of time series data and generating powerful descriptive and predictive insights. COMPUTERS / Data Modeling & Design COMPUTERS / Programming Languages / Python Prakash, Dr. PKS Sonstige oth |
| spellingShingle | Pal, Dr. Avishek Practical Time Series Analysis Master Time Series Data Processing, Visualization, and Modeling using Python COMPUTERS / Data Modeling & Design COMPUTERS / Programming Languages / Python |
| title | Practical Time Series Analysis Master Time Series Data Processing, Visualization, and Modeling using Python |
| title_auth | Practical Time Series Analysis Master Time Series Data Processing, Visualization, and Modeling using Python |
| title_exact_search | Practical Time Series Analysis Master Time Series Data Processing, Visualization, and Modeling using Python |
| title_exact_search_txtP | Practical Time Series Analysis Master Time Series Data Processing, Visualization, and Modeling using Python |
| title_full | Practical Time Series Analysis Master Time Series Data Processing, Visualization, and Modeling using Python Pal, Dr. Avishek |
| title_fullStr | Practical Time Series Analysis Master Time Series Data Processing, Visualization, and Modeling using Python Pal, Dr. Avishek |
| title_full_unstemmed | Practical Time Series Analysis Master Time Series Data Processing, Visualization, and Modeling using Python Pal, Dr. Avishek |
| title_short | Practical Time Series Analysis |
| title_sort | practical time series analysis master time series data processing visualization and modeling using python |
| title_sub | Master Time Series Data Processing, Visualization, and Modeling using Python |
| topic | COMPUTERS / Data Modeling & Design COMPUTERS / Programming Languages / Python |
| topic_facet | COMPUTERS / Data Modeling & Design COMPUTERS / Programming Languages / Python |
| work_keys_str_mv | AT paldravishek practicaltimeseriesanalysismastertimeseriesdataprocessingvisualizationandmodelingusingpython AT prakashdrpks practicaltimeseriesanalysismastertimeseriesdataprocessingvisualizationandmodelingusingpython |