國立高雄大學圖資館 |

語系: 繁體中文

說明(常見問題)

圖資館首頁

登入

回首頁

切換: 標籤 | MARC模式 | ISBD

Practical time series analysis :pred...

Nielsen, Aileen,

Practical time series analysis :prediction with statistics and machine learning /

紀錄類型:	書目-語言資料,印刷品 : Monograph/item
正題名/作者:	Practical time series analysis :Aileen Nielsen.
其他題名:	prediction with statistics and machine learning /
作者:	Nielsen, Aileen,
出版者:	Sebastopol, CA :O'Reilly Media, Inc.,2019.
面頁冊數:	xvi, 480 p. :ill. ;24 cm.
附註:	"October 2019: First Edition"--Title page verso.
標題:	Machine learning.
ISBN:	9781492041658 (pbk.) :

Practical time series analysis :prediction with statistics and machine learning /
Nielsen, Aileen,

Practical time series analysis :prediction with statistics and machine learning /Aileen Nielsen. - 1st ed. - Sebastopol, CA :O'Reilly Media, Inc.,2019. - xvi, 480 p. :ill. ;24 cm.

"October 2019: First Edition"--Title page verso.

Includes bibliographical references and index.

Time series: an overview and a quick history -- Finding and wrangling time series data -- Exploratory data analysis for time series -- Simulating time series data -- Storing temporal data -- Statistical models for time series -- State space models for time series -- Generating and selecting features for a time series -- Machine learning for time series -- Deep learning for time series -- Measuring error -- Performance considerations in fitting and serving time series models -- Healthcare applicaitons -- Financial applications -- Time series for government -- Time series packages -- Forecasts about forecasting.

"Time series data analysis is increasingly important due to the massive production of such data through the internet of things, the digitalization of healthcare, and the rise of smart cities. As continuous monitoring and data collection become more common, the need for competent time series analysis with both statistical and machine learning techniques will increase. Covering innovations in time series data analysis and use cases from the real world, this practical guide will help you solve the most common data engineering and analysis challenges in time series, using both traditional statistical and modern machine learning techniques. Author Aileen Nielsen offers an accessible, well-rounded introduction to time series in both R and Python that will have data scientists, software engineers, and researchers up and running quickly."--Amazon.com.

ISBN: 9781492041658 (pbk.) :$69.99

Nat. Bib. No.: GBB9I6701bnb

Nat. Bib. Agency Control No.: 019612255UkSubjects--Topical Terms:

188639
Machine learning.

LC Class. No.: QA280 / .N54 2019

Dewey Class. No.: 519.55

Practical time series analysis :prediction with statistics and machine learning /
LDR:02391nam a2200289 a 4500 001 571041
003 OCoLC
005 20200807032008.0
008 200908s2019 caua b 001 0 eng d
015 $a GBB9I6701 $2 bnb
016 7 $a 019612255 $2 Uk
020 $a 9781492041658 (pbk.) : $c $69.99
020 $a 1492041653 (pbk.)
023 5 6 $a cam a2200277 a 450
035 $a (OCoLC)1065917890
035 $a on1065917890
040 $a YDX $b eng $c YDX $d OCLCQ $d BDX $d UOK $d JRZ $d GZN $d HCO $d UKMGB $d OCLCF
050 $a QA280 $b .N54 2019
082 0 4 $a 519.55 $2 23
082 0 4 $a 006.31 $2 23
100 1 $a Nielsen, Aileen, $e author. $3 857871
245 1 0 $a Practical time series analysis : $b prediction with statistics and machine learning / $c Aileen Nielsen.
250 $a 1st ed.
260 $a Sebastopol, CA : $b O'Reilly Media, Inc., $c 2019.
300 $a xvi, 480 p. : $b ill. ; $c 24 cm.
500 $a "October 2019: First Edition"--Title page verso.
504 $a Includes bibliographical references and index.
505 0 $a Time series: an overview and a quick history -- Finding and wrangling time series data -- Exploratory data analysis for time series -- Simulating time series data -- Storing temporal data -- Statistical models for time series -- State space models for time series -- Generating and selecting features for a time series -- Machine learning for time series -- Deep learning for time series -- Measuring error -- Performance considerations in fitting and serving time series models -- Healthcare applicaitons -- Financial applications -- Time series for government -- Time series packages -- Forecasts about forecasting.
520 $a "Time series data analysis is increasingly important due to the massive production of such data through the internet of things, the digitalization of healthcare, and the rise of smart cities. As continuous monitoring and data collection become more common, the need for competent time series analysis with both statistical and machine learning techniques will increase. Covering innovations in time series data analysis and use cases from the real world, this practical guide will help you solve the most common data engineering and analysis challenges in time series, using both traditional statistical and modern machine learning techniques. Author Aileen Nielsen offers an accessible, well-rounded introduction to time series in both R and Python that will have data scientists, software engineers, and researchers up and running quickly."--Amazon.com.
650 0 $a Machine learning. $3 188639
650 0 $a Time-series analysis $x Data processing. $3 190935
650 0 $a Python (Computer program language) $3 215247
650 0 $a R (Computer program language) $3 210846