1. 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).