{"product_id":"time-series-forecasting-in-python-paperback","title":"Time Series Forecasting in Python (Paperback)","description":"\u003cp\u003e\u003cb\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\u003e\u003c\/p\u003e\u003cp\u003eIn \u003ci\u003eTime Series Forecasting in Python\u003c\/i\u003e you will learn how to:\u003c\/p\u003e\u003cp\u003e    Recognize a time series forecasting problem and build a performant predictive model\u003cbr\u003e    Create univariate forecasting models that account for seasonal effects and external variables\u003cbr\u003e    Build multivariate forecasting models to predict many time series at once\u003cbr\u003e    Leverage large datasets by using deep learning for forecasting time series\u003cbr\u003e    Automate the forecasting process\u003c\/p\u003e\u003cp\u003e\u003ci\u003eTime Series Forecasting in Python\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\/p\u003e\u003cp\u003e\u003cstrong\u003eAbout the technology\u003c\/strong\u003e\u003cbr\u003eYou can predict the future—with a little help from Python, deep learning, and time series data! Time series forecasting is a technique for modeling time-centric data to identify upcoming events. New Python libraries and powerful deep learning tools make accurate time series forecasts easier than ever before.\u003c\/p\u003e\u003cp\u003e\u003cstrong\u003eAbout the book\u003c\/strong\u003e\u003cbr\u003e\u003ci\u003eTime Series Forecasting in Python\u003c\/i\u003e teaches you how to get immediate, meaningful predictions from time-based data such as logs, customer analytics, and other event streams. In this accessible book, you’ll learn statistical and deep learning methods for time series forecasting, fully demonstrated with annotated Python code. Develop your skills with projects like predicting the future volume of drug prescriptions, and you’ll soon be ready to build your own accurate, insightful forecasts.\u003c\/p\u003e\u003cp\u003eWhat's inside\u003c\/p\u003e\u003cp\u003e    Create models for seasonal effects and external variables\u003cbr\u003e    Multivariate forecasting models to predict multiple time series\u003cbr\u003e    Deep learning for large datasets\u003cbr\u003e    Automate the forecasting process\u003c\/p\u003e\u003cp\u003e\u003cstrong\u003eAbout the reader\u003c\/strong\u003e\u003cbr\u003eFor data scientists familiar with Python and TensorFlow.\u003c\/p\u003e\u003cp\u003eAbout the author\u003cbr\u003e\u003cb\u003eMarco Peixeiro\u003c\/b\u003e is a seasoned data science instructor who has worked as a data scientist for one of Canada’s largest banks.\u003c\/p\u003e\u003cp\u003e\u003cstrong\u003eTable of Contents\u003c\/strong\u003e\u003cbr\u003ePART 1 TIME WAITS FOR NO ONE\u003cbr\u003e1 Understanding time series forecasting\u003cbr\u003e2 A naive prediction of the future\u003cbr\u003e3 Going on a random walk\u003cbr\u003ePART 2 FORECASTING WITH STATISTICAL MODELS\u003cbr\u003e4 Modeling a moving average process\u003cbr\u003e5 Modeling an autoregressive process\u003cbr\u003e6 Modeling complex time series\u003cbr\u003e7 Forecasting non-stationary time series\u003cbr\u003e8 Accounting for seasonality\u003cbr\u003e9 Adding external variables to our model\u003cbr\u003e10 Forecasting multiple time series\u003cbr\u003e11 Capstone: Forecasting the number of antidiabetic drug prescriptions in Australia\u003cbr\u003ePART 3 LARGE-SCALE FORECASTING WITH DEEP LEARNING\u003cbr\u003e12 Introducing deep learning for time series forecasting\u003cbr\u003e13 Data windowing and creating baselines for deep learning\u003cbr\u003e14 Baby steps with deep learning\u003cbr\u003e15 Remembering the past with LSTM\u003cbr\u003e16 Filtering a time series with CNN\u003cbr\u003e17 Using predictions to make more predictions\u003cbr\u003e18 Capstone: Forecasting the electric power consumption of a household\u003cbr\u003ePART 4 AUTOMATING FORECASTING AT SCALE\u003cbr\u003e19 Automating time series forecasting with Prophet\u003cbr\u003e20 Capstone: Forecasting the monthly average retail price of steak in Canada\u003cbr\u003e21 Going above and beyond\u003c\/p\u003e\u003cp\u003e\u003c\/p\u003e","brand":"Manning Publications","offers":[{"title":"Paperback","offer_id":50506272800838,"sku":"9781617299889","price":5318.0,"currency_code":"INR","in_stock":true},{"title":"E-Book","offer_id":50506272833606,"sku":"9781617299889-2","price":5121.0,"currency_code":"INR","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0754\/2797\/1142\/files\/41GOJ_MdImL._SX397_BO1_204_203_200.jpg?v=1790324806","url":"https:\/\/cb-india.com\/products\/time-series-forecasting-in-python-paperback","provider":"Computer Bookshop (India) Pvt Ltd","version":"1.0","type":"link"}