×
Dodano do koszyka:
Pozycja znajduje się w koszyku, zwiększono ilość tej pozycji:
Zakupiłeś już tę pozycję:
Książkę możesz pobrać z biblioteki w panelu użytkownika
Pozycja znajduje się w koszyku
Przejdź do koszyka

Zawartość koszyka

ODBIERZ TWÓJ BONUS :: »

Hands-On Time Series Analysis with R. Perform time series analysis and forecasting using R

(ebook) (audiobook) (audiobook) Książka w języku 1
Autor:
Rami Krispin
Hands-On Time Series Analysis with R. Perform time series analysis and forecasting using R Rami Krispin - okladka książki

Hands-On Time Series Analysis with R. Perform time series analysis and forecasting using R Rami Krispin - okladka książki

Hands-On Time Series Analysis with R. Perform time series analysis and forecasting using R Rami Krispin - audiobook MP3

Hands-On Time Series Analysis with R. Perform time series analysis and forecasting using R Rami Krispin - audiobook CD

Ocena:
Bądź pierwszym, który oceni tę książkę
Stron:
448
Dostępne formaty:
     PDF
     ePub
     Mobi

Ebook (98,10 zł najniższa cena z 30 dni)

109,00 zł (-73%)
29,90 zł

Dodaj do koszyka lub Kup na prezent Kup 1-kliknięciem

(98,10 zł najniższa cena z 30 dni)

Przenieś na półkę

Do przechowalni

Time-series analysis is the art of extracting meaningful insights from, and revealing patterns in, time-series data using statistical and data visualization approaches. These insights and patterns can then be utilized to explore past events and forecast future values in the series.
This book explores the basics of time-series analysis with R and lays the foundation you need to build forecasting models. You will learn how to preprocess raw time-series data and clean and manipulate data with packages such as stats, lubridate, xts, and zoo. You will analyze data using both descriptive statistics and rich data visualization tools in R including the TSstudio, plotly, and ggplot2 packages. The book then delves into traditional forecasting models such as time-series linear regression, exponential smoothing (Holt, Holt-Winter, and more) and Auto-Regressive Integrated Moving Average (ARIMA) models with the stats and forecast packages. You'll also work on advanced time-series regression models with machine learning algorithms such as random forest and Gradient Boosting Machine using the h2o package.
By the end of this book, you will have developed the skills necessary for exploring your data, identifying patterns, and building a forecasting model using various traditional and machine learning methods.

Wybrane bestsellery

O autorze książki

Rami Krispin is a data scientist at a major Silicon Valley company, where he focuses on time series analysis and forecasting. In his free time, he also develops open source tools and is the author of several R packages, including the TSstudio package for time series analysis and forecasting applications. Rami holds an MA in Applied Economics and an MS in actuarial mathematics from the University of MichiganAnn Arbor.

Packt Publishing - inne książki

Zamknij

Przenieś na półkę

Proszę czekać...
ajax-loader

Zamknij

Wybierz metodę płatności

Ebook
29,90 zł
Dodaj do koszyka
Zamknij Pobierz aplikację mobilną Ebookpoint