Time Series Forecasting Accelerator

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Presentation transcript:

Time Series Forecasting Accelerator An engine to forecast time series values Uses historical trend, seasonal variations, and cyclical patterns A number of simple and complex models included Multiple dimensions and metrics used for forecast Engine and UI developed on RStudio using the Shiny interface FEATURES Uses 12 different forecast models, such as moving averages, exponential smoothing, neural networks, and ensemble machine learning. Aggregates daily data to weekly, monthly, and yearly. Offers multiple accuracy measures and train/test splits. Calculates forecast estimates and confidence intervals. APPLICATION AREAS Sales Item sales forecasts over time for multiple products and/or categories. Pricing Raw material/commodity pricing trends, forecasts, and seasonal impacts. Other Services Advertising (impressions forecasting), Meteorology (prediction of rain or weather patterns), Finance (stock market prices).