Time-Series-Forecasting-of-Demand

A statistical library designed to fill the void in Python's time series analysis capabilities, including the equivalent of R's auto.arima function.

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

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

Hierarchical Time Series Forecasting with a familiar API

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

ARIMA, SARIMA, SARIMAX and AutoARIMA models for time series analysis and forecasting in the browser and Node.js

Full-stack Highly Scalable Cloud-native Machine Learning system for demand forecasting with realtime data streaming, inference, retraining loop, and more

I perform time series analysis of data from scratch. I also implement The Autoregressive (AR) Model, The Moving Average (MA) Model, The Autoregressive Moving Average (ARMA) Model, The Autoregressive Integrated Moving Average (ARIMA) Model, The ARCH Model, The GARCH model, Auto ARIMA, forecasting and exploring a business case.

Internship project

Time Series Forecasting for the M5 Competition