{"product_id":"hands-on-time-series-analysis-with-r-pstrong-perform-time-series-analysis-and-forecasting-using-r-p","title":"Hands-On Time Series Analysis with R","description":"\u003cp style=\"margin: 0px 0px 14px; padding: 0px; font-family: \" amazon ember arial sans-serif font-size:=\"\"\u003e\u003cb\u003eBuild efficient forecasting models using traditional time series models and machine learning algorithms.\u003c\/b\u003e\u003c\/p\u003e\u003ch4 style=\"margin: 0px; padding: 0px 0px 4px; font-family: Arial, sans-serif; text-rendering: optimizelegibility; font-size: 14px;\"\u003e\u003cstrong\u003eKey Features\u003c\/strong\u003e\u003c\/h4\u003e\u003cul style=\"margin: 0px 0px 18px 20px; padding-right: 0px; padding-left: 0px; font-family: \" amazon ember arial sans-serif font-size:=\"\"\u003e\n\u003cli style=\"margin: 0px 0px 0px 20px; overflow-wrap: break-word;\"\u003ePerform time series analysis and forecasting using R packages such as Forecast and h2o\u003c\/li\u003e\n\u003cli style=\"margin: 0px 0px 0px 20px; overflow-wrap: break-word;\"\u003eDevelop models and find patterns to create visualizations using the TSstudio and plotly packages\u003c\/li\u003e\n\u003cli style=\"margin: 0px 0px 0px 20px; overflow-wrap: break-word;\"\u003eMaster statistics and implement time-series methods using examples mentioned\u003c\/li\u003e\n\u003c\/ul\u003e\u003ch4 style=\"margin: 0px; padding: 0px 0px 4px; font-family: Arial, sans-serif; text-rendering: optimizelegibility; font-size: 14px;\"\u003e\u003cstrong\u003eBook Description\u003c\/strong\u003e\u003c\/h4\u003e\u003cp style=\"margin: 0px 0px 14px; padding: 0px; font-family: \" amazon ember arial sans-serif font-size:=\"\"\u003eTime 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.\u003c\/p\u003e\u003cp style=\"margin: -4px 0px 14px; padding: 0px; font-family: \" amazon ember arial sans-serif font-size:=\"\"\u003eThis book explores the basics of time series analysis with R and lays the foundations 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 and extract meaningful information from it using both descriptive statistics and rich data visualization tools in R such as the TSstudio, plotly, and ggplot2 packages. The later section of the book 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 cover advanced time series regression models with machine learning algorithms such as Random Forest and Gradient Boosting Machine using the h2o package.\u003c\/p\u003e\u003cp style=\"margin: -4px 0px 14px; padding: 0px; font-family: \" amazon ember arial sans-serif font-size:=\"\"\u003eBy the end of this book, you will have the skills needed to explore your data, identify patterns, and build a forecasting model using various traditional and machine learning methods.\u003c\/p\u003e\u003ch4 style=\"margin: 0px; padding: 0px 0px 4px; font-family: Arial, sans-serif; text-rendering: optimizelegibility; font-size: 14px;\"\u003e\u003cstrong\u003eWhat you will learn\u003c\/strong\u003e\u003c\/h4\u003e\u003cul style=\"margin: 0px 0px 18px 20px; padding-right: 0px; padding-left: 0px; font-family: \" amazon ember arial sans-serif font-size:=\"\"\u003e\n\u003cli style=\"margin: 0px 0px 0px 20px; overflow-wrap: break-word;\"\u003eVisualize time series data and derive better insights\u003c\/li\u003e\n\u003cli style=\"margin: 0px 0px 0px 20px; overflow-wrap: break-word;\"\u003eExplore auto-correlation and master statistical techniques\u003c\/li\u003e\n\u003cli style=\"margin: 0px 0px 0px 20px; overflow-wrap: break-word;\"\u003eUse time series analysis tools from the stats, TSstudio, and forecast packages\u003c\/li\u003e\n\u003cli style=\"margin: 0px 0px 0px 20px; overflow-wrap: break-word;\"\u003eExplore and identify seasonal and correlation patterns\u003c\/li\u003e\n\u003cli style=\"margin: 0px 0px 0px 20px; overflow-wrap: break-word;\"\u003eWork with different time series formats in R\u003c\/li\u003e\n\u003cli style=\"margin: 0px 0px 0px 20px; overflow-wrap: break-word;\"\u003eExplore time series models such as ARIMA, Holt-Winters, and more\u003c\/li\u003e\n\u003cli style=\"margin: 0px 0px 0px 20px; overflow-wrap: break-word;\"\u003eEvaluate high-performance forecasting solutions\u003c\/li\u003e\n\u003c\/ul\u003e\u003ch4 style=\"margin: 0px; padding: 0px 0px 4px; font-family: Arial, sans-serif; text-rendering: optimizelegibility; font-size: 14px;\"\u003e\u003cstrong\u003eWho this book is for\u003c\/strong\u003e\u003c\/h4\u003e\u003cp style=\"margin: 0px 0px 14px; padding: 0px; font-family: \" amazon ember arial sans-serif font-size:=\"\"\u003eHands-On Time Series Analysis with R is ideal for data analysts, data scientists, and all R developers who are looking to perform time series analysis to predict outcomes effectively. A basic knowledge of statistics is required; some knowledge in R is expected, but not mandatory.\u003c\/p\u003e\u003ch4 style=\"margin: 0px; padding: 0px 0px 4px; font-family: Arial, sans-serif; text-rendering: optimizelegibility; font-size: 14px;\"\u003e\u003cstrong\u003eTable of Contents\u003c\/strong\u003e\u003c\/h4\u003e\u003col style=\"color: rgb(136, 136, 136); margin-top: 0px; margin-right: 0px; margin-left: 22px; padding-right: 0px; padding-left: 0px; font-family: \" amazon ember arial sans-serif font-size:=\"\" margin-bottom:=\"\"\u003e\n\u003cli style=\"margin: 0px; overflow-wrap: break-word;\"\u003e\u003cspan style=\"color:#000000;\"\u003eIntroduction to Time Series Analysis and R\u003c\/span\u003e\u003c\/li\u003e\n\u003cli style=\"margin: 0px; overflow-wrap: break-word;\"\u003e\u003cspan style=\"color:#000000;\"\u003eWorking with Date and Time Objects\u003c\/span\u003e\u003c\/li\u003e\n\u003cli style=\"margin: 0px; overflow-wrap: break-word;\"\u003e\u003cspan style=\"color:#000000;\"\u003eThe Time Series Object\u003c\/span\u003e\u003c\/li\u003e\n\u003cli style=\"margin: 0px; overflow-wrap: break-word;\"\u003e\u003cspan style=\"color:#000000;\"\u003eWorking with zoo and xts Objects\u003c\/span\u003e\u003c\/li\u003e\n\u003cli style=\"margin: 0px; overflow-wrap: break-word;\"\u003e\u003cspan style=\"color:#000000;\"\u003eDecomposition of Time Series Data\u003c\/span\u003e\u003c\/li\u003e\n\u003cli style=\"margin: 0px; overflow-wrap: break-word;\"\u003e\u003cspan style=\"color:#000000;\"\u003eSeasonality Analysis\u003c\/span\u003e\u003c\/li\u003e\n\u003cli style=\"margin: 0px; overflow-wrap: break-word;\"\u003e\u003cspan style=\"color:#000000;\"\u003eCorrelation Analysis\u003c\/span\u003e\u003c\/li\u003e\n\u003cli style=\"margin: 0px; overflow-wrap: break-word;\"\u003e\u003cspan style=\"color:#000000;\"\u003eForecasting Strategies\u003c\/span\u003e\u003c\/li\u003e\n\u003cli style=\"margin: 0px; overflow-wrap: break-word;\"\u003e\u003cspan style=\"color:#000000;\"\u003eForecasting with Linear Regression\u003c\/span\u003e\u003c\/li\u003e\n\u003cli style=\"margin: 0px; overflow-wrap: break-word;\"\u003e\u003cspan style=\"color:#000000;\"\u003eForecasting with Exponential Smoothing Models\u003c\/span\u003e\u003c\/li\u003e\n\u003cli style=\"margin: 0px; overflow-wrap: break-word;\"\u003e\u003cspan style=\"color:#000000;\"\u003eForecasting with ARIMA Models\u003c\/span\u003e\u003c\/li\u003e\n\u003cli style=\"margin: 0px; overflow-wrap: break-word;\"\u003e\u003cspan style=\"color:#000000;\"\u003eForecasting with Machine Learning Models\u003c\/span\u003e\u003c\/li\u003e\n\u003c\/ol\u003e","brand":"Packt Publishing","offers":[{"title":"Default Title","offer_id":50506204348486,"sku":"9781788629157","price":2319.0,"currency_code":"INR","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0754\/2797\/1142\/files\/51qCC5NRmZL._SX404_BO1_204_203_200.jpg?v=1790323009","url":"https:\/\/cb-india.com\/products\/hands-on-time-series-analysis-with-r-pstrong-perform-time-series-analysis-and-forecasting-using-r-p","provider":"Computer Bookshop (India) Pvt Ltd","version":"1.0","type":"link"}