{"product_id":"time-series-forecasting-with-machine-learning-in-r-from-foundation-to-advanced-methods-9798269521404","title":"Time Series Forecasting with Machine Learning in R: From Foundation to Advanced Methods","description":"\u003cp\u003e • Author(s): Joseph Solomon | Toyin O. Oguntola | Dorcas O. Folarin\u003cbr\u003e • Publisher: Independently Published\u003cbr\u003e • Publisher Imprint: Independently Published\u003cbr\u003e • BISAC: Statistics\u003c\/p\u003e\u003cp\u003e\u003cb\u003e\u003ci\u003eTime Series Forecasting with Machine Learning in R\u003c\/i\u003e\u003c\/b\u003e bridges the gap between traditional statistical forecasting and cutting-edge machine learning methods. Written in a practical and applied style, this book empowers readers to build, evaluate, and deploy predictive models for time-dependent data using the powerful R ecosystem.\u003cbr\u003eStarting from the foundations of time series theory, readers will learn how to visualize, decompose, and understand patterns such as trend and seasonality. The book introduces classic models like ARIMA and exponential smoothing, before diving into advanced machine learning and deep learning techniques - including random forests, gradient boosting, LSTM networks, and hybrid forecasting systems.\u003cbr\u003eWith hands-on R code examples, real-world datasets, and clear explanations, this book is perfect for students, researchers, and data professionals who want to master predictive analytics for business, economics, finance, healthcare, and environmental data.\u003cbr\u003eBy the end of the book, readers will be able to: \u003c\/p\u003e\u003cul\u003e\n\u003cli\u003ePreprocess and explore time series data using \u003cb\u003eTidyverse\u003c\/b\u003e and \u003cb\u003etsibble\u003c\/b\u003e packages.\u003c\/li\u003e\n\u003cli\u003eBuild statistical models such as \u003cb\u003eARIMA\u003c\/b\u003e, \u003cb\u003eETS\u003c\/b\u003e, and \u003cb\u003eSARIMA\u003c\/b\u003e.\u003c\/li\u003e\n\u003cli\u003eApply machine learning algorithms for forecasting with \u003cb\u003ecaret\u003c\/b\u003e, \u003cb\u003emlr3\u003c\/b\u003e, and \u003cb\u003etidymodels\u003c\/b\u003e.\u003c\/li\u003e\n\u003cli\u003eEvaluate forecast accuracy using industry-standard metrics.\u003c\/li\u003e\n\u003cli\u003eCombine multiple models for robust and interpretable predictions.\u003c\/li\u003e\n\u003cli\u003eDevelop end-to-end forecasting pipelines in R for real-world applications.\u003c\/li\u003e\n\u003c\/ul\u003eWhether you are a beginner in time series or an experienced data scientist seeking to expand your forecasting toolkit, this comprehensive guide provides both the theoretical background and the hands-on experience needed to make accurate, data-driven forecasts.","brand":"Atlantic Books","offers":[{"title":"Paperback","offer_id":46332058665111,"sku":"9798269521404","price":1768.0,"currency_code":"INR","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0666\/3471\/1191\/files\/9798269521404.webp?v=1768725079","url":"https:\/\/atlanticbooks.com\/products\/time-series-forecasting-with-machine-learning-in-r-from-foundation-to-advanced-methods-9798269521404","provider":"Atlantic Books","version":"1.0","type":"link"}