exponential-smoothing

Lightning ⚡️ fast forecasting with statistical and econometric models.

A Python package for Bayesian forecasting with object-oriented design and probabilistic models under the hood.

PyTorch code for ETSformer: Exponential Smoothing Transformers for Time-series Forecasting

StateSpaceModels.jl is a Julia package for time-series analysis using state-space models.

Hierarchical Time Series Forecasting with a familiar API

Book and material for the course "Time series analysis with Python" (STA-2003)

Implementation of ETSformer, state of the art time-series Transformer, in Pytorch

The set of functions used for time series analysis and in forecasting.

Forecasted product sales using time series models such as Holt-Winters, SARIMA and causal methods, e.g. Regression. Evaluated performance of models using forecasting metrics such as, MAE, RMSE, MAPE and concluded that Linear Regression model produced the best MAPE in comparison to other models

Real-time time series prediction library with standalone server

Forecasting Monthly Sales of French Champagne - Perrin Freres

Time Series Forecasting Methods — A collection of Python implementations for essential time series forecasting techniques, including Simple, Double, Triple Exponential Smoothing, and Moving Averages.

Exponential Smoothing, SARIMA, Facebook Prophet

Forecasting Time Series with Moving Average and Exponential Smoothing

Borealis AI mentored water consumption prediction machine learning web application!

A learning tool to demonstrate the process of financial forecasting, budgeting, and analysis.

Holt-Winters exponential smoothing implemented in Go.

Theta methods for time series forcasting

The Korea National Oil Corporation was interested in purchasing shale gas wells from the United States and wanted to predict their production to select wells that maximize profit.