We live in a serendipitous era where the explosion in the quantum of data collected and a renewed interest in data-driven techniques such as machine learning (ML), has changed the landscape of ...

Prophet empowers Python and R developers to build scalable time series forecasts. This book will help you to implement Prophet’s cutting-edge forecasting techniques to model future data with high ...

Book Abstract: Build predictive models from time-based patterns in your data. Master statistical models including new deep learning approaches for time series forecasting. Recognize a time series ...

Master statistical models including new deep learning approaches for time series forecasting. Recognize a time series forecasting problem and build a performant predictive model Create univariate ...

Time series data is a sequence of observations collected at regular intervals, such as stock prices, weather patterns, or sensor readings. Forecasting time series data means predicting future ...

You will be redirected to our submission process. In recent years, the application of deep learning methods for time series forecasting has grown significantly, driven by their ability to capture ...

Our study sought to construct an adequate model and to forecast monthly ED visits. Methods We retrospectively gathered monthly ED visits from January 2009 to December 2016 to carry out a time series ...