{"product_id":"time-series-forecasting-in-python","title":"Time Series Forecasting In Python","description":"\u003cdiv class=\"product-page-section\" style='box-sizing: border-box; margin-bottom: 36px; color: rgb(51, 51, 51); font-family: Lato, -apple-system, BlinkMacSystemFont, \"avenir next\", avenir, \"helvetica neue\", helvetica, Ubuntu, roboto, noto, \"segoe ui\", arial, sans-serif;'\u003e  \u003cdiv class=\"product-page-section\" style=\"box-sizing: border-box; margin-bottom: 0px; padding-bottom: 0px;\"\u003e   \u003cb style=\"font-size: 17.25px; box-sizing: border-box;\"\u003eBuild predictive models from time-based patterns in your data. Master statistical models including new deep learning approaches for time series forecasting.\u003c\/b\u003e   \u003cbr style=\"box-sizing: border-box;\"\u003e   \u003cbr style=\"box-sizing: border-box;\"\u003e   \u003cspan style=\"font-size: 17.25px;\"\u003eIn \u003c\/span\u003e   \u003ci style=\"font-size: 17.25px; box-sizing: border-box;\"\u003eT\u003cb\u003eime Series Forecasting in Python\u003c\/b\u003e\u003c\/i\u003e   \u003cspan style=\"font-size: 17.25px;\"\u003e you will learn how to:\u003c\/span\u003e   \u003cbr style=\"box-sizing: border-box;\"\u003e   \u003cbr style=\"box-sizing: border-box;\"\u003e   \u003cul style=\"font-size: 17.25px; box-sizing: border-box; margin-top: 0px; margin-bottom: 10.5px; padding-left: 17.5px;\"\u003e    \u003cli style=\"box-sizing: border-box;\"\u003eRecognize a time series forecasting problem and build a performant predictive model\u003c\/li\u003e    \u003cli style=\"box-sizing: border-box;\"\u003eCreate univariate forecasting models that account for seasonal effects and external variables\u003c\/li\u003e    \u003cli style=\"box-sizing: border-box;\"\u003eBuild multivariate forecasting models to predict many time series at once\u003c\/li\u003e    \u003cli style=\"box-sizing: border-box;\"\u003eLeverage large datasets by using deep learning for forecasting time series\u003c\/li\u003e    \u003cli style=\"box-sizing: border-box;\"\u003eAutomate the forecasting process\u003c\/li\u003e   \u003c\/ul\u003e   \u003cbr style=\"box-sizing: border-box;\"\u003e   \u003ci style=\"box-sizing: border-box; margin-bottom: 0px; padding-bottom: 0px;\"\u003e\u003cb style=\"\"\u003e\u003cfont size=\"5\"\u003eDESCRIPTION \u003c\/font\u003e\u003c\/b\u003e\u003c\/i\u003e  \u003c\/div\u003e  \u003cdiv class=\"product-page-section\" style=\"font-size: 17.25px; box-sizing: border-box; margin-bottom: 0px; padding-bottom: 0px;\"\u003e   \u003ci style=\"box-sizing: border-box; margin-bottom: 0px; padding-bottom: 0px;\"\u003e\u003cb\u003eTime Series Forecasting in Python\u003c\/b\u003e teaches you to build powerful predictive models from time-based data. Every model you create is relevant, useful, and easy to implement with Python. You''ll explore interesting real-world datasets like Google''s daily stock price and economic data for the USA, quickly progressing from the basics to developing large-scale models that use deep learning tools like TensorFlow.Time Series Forecasting in Python teaches you to apply time series forecasting and get immediate, meaningful predictions. You''ll learn both traditional statistical and new deep learning models for time series forecasting, all fully illustrated with Python source code.\u003c\/i\u003e  \u003c\/div\u003e  \u003cdiv class=\"product-page-section\" style=\"font-size: 17.25px; box-sizing: border-box; margin-bottom: 0px; padding-bottom: 0px;\"\u003e   \u003ci style=\"box-sizing: border-box; margin-bottom: 0px; padding-bottom: 0px;\"\u003e\u003cbr\u003e\u003c\/i\u003e  \u003c\/div\u003e  \u003cdiv class=\"product-page-section\" style=\"font-size: 17.25px; box-sizing: border-box; margin-bottom: 0px; padding-bottom: 0px;\"\u003e   \u003ci style=\"box-sizing: border-box; margin-bottom: 0px; padding-bottom: 0px;\"\u003e\u003cb\u003eTime Series Forecasting in Python\u003c\/b\u003e\u003c\/i\u003e teaches you to build powerful predictive models from time-based data. Every model you create is relevant, useful, and easy to implement with Python. You''ll explore interesting real-world datasets like Google''s daily stock price and economic data for the USA, quickly progressing from the basics to developing large-scale models that use deep learning tools like TensorFlow.  \u003c\/div\u003e \u003c\/div\u003e \u003cdiv class=\"product-page-section\" style='box-sizing: border-box; margin-bottom: 36px; color: rgb(51, 51, 51); font-family: Lato, -apple-system, BlinkMacSystemFont, \"avenir next\", avenir, \"helvetica neue\", helvetica, Ubuntu, roboto, noto, \"segoe ui\", arial, sans-serif; font-size: 17.25px;'\u003e  \u003ch2 style=\"box-sizing: border-box; line-height: 1.1; color: inherit; margin: 0px 0px 10px; font-size: 27px; text-transform: lowercase;\"\u003eabout the technology\u003c\/h2\u003e  \u003ca name=\"about-the-technology\" class=\"anchor\" style=\"box-sizing: border-box; color: rgb(64, 127, 191); visibility: hidden; display: block; position: relative; margin-bottom: 0px; padding-bottom: 0px;\"\u003e\u003c\/a\u003eTime series forecasting reveals hidden trends and makes predictions about the future from your data. This powerful technique has proven incredibly valuable across multiple fields—from tracking business metrics, to healthcare and the sciences. Modern Python libraries and powerful deep learning tools have opened up new methods and utilities for making practical time series forecasts. \u003c\/div\u003e \u003cdiv class=\"product-page-section\" style='box-sizing: border-box; margin-bottom: 36px; color: rgb(51, 51, 51); font-family: Lato, -apple-system, BlinkMacSystemFont, \"avenir next\", avenir, \"helvetica neue\", helvetica, Ubuntu, roboto, noto, \"segoe ui\", arial, sans-serif; font-size: 17.25px;'\u003e  \u003ch2 style=\"box-sizing: border-box; line-height: 1.1; color: inherit; margin: 0px 0px 10px; font-size: 27px; text-transform: lowercase;\"\u003eabout the book\u003c\/h2\u003e  \u003ca name=\"about-the-book\" class=\"anchor\" style=\"box-sizing: border-box; color: rgb(64, 127, 191); visibility: hidden; display: block; position: relative;\"\u003e\u003c\/a\u003e  \u003ci style=\"box-sizing: border-box; margin-bottom: 0px; padding-bottom: 0px;\"\u003e\u003cb\u003eTime Series Forecasting in Python\u003c\/b\u003e\u003c\/i\u003e teaches you to apply time series forecasting and get immediate, meaningful predictions. You''ll learn both traditional statistical and new deep learning models for time series forecasting, all fully illustrated with Python source code. Test your skills with hands-on projects for forecasting air travel, volume of drug prescriptions, and the earnings of Johnson \u0026amp; Johnson. By the time you''re done, you''ll be ready to build accurate and insightful forecasting models with tools from the Python ecosystem. \u003c\/div\u003e","brand":"MediaPlace","offers":[{"title":"Default Title","offer_id":57312401752446,"sku":"NW9781617299889","price":53.95,"currency_code":"EUR","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0817\/1379\/1261\/files\/9781617299889.jpg?v=1778587948","url":"https:\/\/mediaplace.com\/en-eu\/products\/time-series-forecasting-in-python","provider":"MediaPlace","version":"1.0","type":"link"}