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    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

    Wydawnictwo:
    Packt Publishing (Z chęcią przeczytam książkę w języku polskim)
    Ocena:
    Bądź pierwszym, który oceni tę książkę
    Stron:
    448
    Dostępne formaty:
         PDF
         ePub
         Mobi
    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.

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    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.

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