{"product_id":"practical-time-series-forecasting-with-python-a-hands-on-guide-paperback","title":"Practical Time Series Forecasting with Python: A Hands-On Guide - Paperback","description":"\u003cdiv\u003e\u003cp style=\"text-align: right;\"\u003e\u003ca href=\"https:\/\/reportcopyrightinfringement.com\/\" target=\"_blank\" rel=\"nofollow\"\u003e\u003cb\u003eReport copyright infringement\u003c\/b\u003e\u003c\/a\u003e\u003c\/p\u003e\u003c\/div\u003e\u003cp\u003eby \u003cb\u003eEric Berger\u003c\/b\u003e (Author), \u003cb\u003eGalit Shmueli\u003c\/b\u003e (Author)\u003c\/p\u003e\u003cp\u003e\u003ci\u003ePractical Time Series Forecasting with Python: A Hands-On Guide\u003c\/i\u003e provides an applied approach to time-series forecasting. Forecasting is an essential component of predictive analytics. The book introduces popular forecasting methods and approaches used in a variety of business applications. \u003c\/p\u003e\u003cp\u003e\u003c\/p\u003eThe book offers clear explanations, practical examples, and end-of-chapter exercises and cases. Readers will learn to use forecasting methods using the free open-source Python software to develop effective forecasting solutions that extract business value from time series data. \u003cp\u003e\u003c\/p\u003eThis edition includes: \u003cul\u003e\n\u003cli\u003ePopular forecasting methods including smoothing algorithms, regression models, ARIMA, neural networks, deep learning, and ensembles\u003c\/li\u003e\n\u003cli\u003eA practical approach to evaluating the performance of forecasting solutions\u003c\/li\u003e\n\u003cli\u003eA business-analytics exposition focused on linking time-series forecasting to business goals\u003c\/li\u003e\n\u003cli\u003eGuided cases for integrating the acquired knowledge using real data\u003c\/li\u003e\n\u003cli\u003eEnd-of-chapter problems to facilitate active learning\u003c\/li\u003e\n\u003cli\u003eData, Python code, and instructor materials on companion website\u003c\/li\u003e\n\u003cli\u003eAffordable and globally-available textbook, available in hardcover, paperback, and ebook formats\u003c\/li\u003e\n\u003c\/ul\u003e\u003ci\u003ePractical Time Series Forecasting with Python: A Hands-On Guide\u003c\/i\u003e is the perfect textbook for upper-undergraduate, graduate and MBA-level courses as well as professional programs in data science and business analytics. The book is also designed for practitioners in the fields of operations research, supply chain management, marketing, economics, information systems, finance, and management.\n            \u003cdiv\u003e\n\u003cstrong\u003eNumber of Pages:\u003c\/strong\u003e 256\u003c\/div\u003e\n            \u003cdiv\u003e\n\u003cstrong\u003eDimensions:\u003c\/strong\u003e 0.54 x 10 x 7 IN\u003c\/div\u003e\n            \u003cdiv\u003e\n\u003cstrong\u003ePublication Date:\u003c\/strong\u003e July 05, 2025\u003c\/div\u003e\n            ","brand":"BooksCloud","offers":[{"title":"Default Title","offer_id":47208806744313,"sku":"9780997847963","price":47.25,"currency_code":"USD","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0789\/2782\/3097\/files\/ANpPmWHBOz9780997847963.webp?v=1768058269","url":"https:\/\/bookscloud.io\/products\/practical-time-series-forecasting-with-python-a-hands-on-guide-paperback","provider":"BooksCloud Book Dropshipping","version":"1.0","type":"link"}