Practical Time Series Analysis

Practical Time Series Analysis - Aileen Nielsen

Practical Time Series Analysis


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 challengesin 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.

You'll get the guidance you need to confidently:

  • Find and wrangle time series data
  • Undertake exploratory time series data analysis
  • Store temporal data
  • Simulate time series data
  • Generate and select features for a time series
  • Measure error
  • Forecast and classify time series with machine or deep learning
  • Evaluate accuracy and performance
Citeste mai mult

-10%

transport gratuit

PRP: 435.13 Lei

!

Acesta este Pretul Recomandat de Producator. Pretul de vanzare al produsului este afisat mai jos.

391.62Lei

391.62Lei

435.13 Lei

Primesti 391 puncte

Important icon msg

Primesti puncte de fidelitate dupa fiecare comanda! 100 puncte de fidelitate reprezinta 1 leu. Foloseste-le la viitoarele achizitii!

Livrare in 2-4 saptamani

Descrierea produsului


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 challengesin 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.

You'll get the guidance you need to confidently:

  • Find and wrangle time series data
  • Undertake exploratory time series data analysis
  • Store temporal data
  • Simulate time series data
  • Generate and select features for a time series
  • Measure error
  • Forecast and classify time series with machine or deep learning
  • Evaluate accuracy and performance
Citeste mai mult

De pe acelasi raft

Parerea ta e inspiratie pentru comunitatea Libris!

Noi suntem despre carti, si la fel este si

Newsletter-ul nostru.

Aboneaza-te la vestile literare si primesti un cupon de -10% pentru viitoarea ta comanda!

*Reducerea aplicata prin cupon nu se cumuleaza, ci se aplica reducerea cea mai mare.

Ma abonez image one
Ma abonez image one