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

List of papers, code and experiments using deep learning for time series forecasting

A toolkit for working with time series in R

AtsPy: Automated Time Series Models in Python (by @firmai)

Extending broom for time series forecasting

An open source library for Fuzzy Time Series in Python

Sky Cast: A Comparison of Modern Techniques for Forecasting Time Series

QGIS toolkit 🧰 for pre- and post-processing 🔨, visualizing 🔍, and running simulations 💻 in the Weather Research and Forecasting (WRF) model 🌀

MSGARCH R Package

Real-time time series prediction library with standalone server

Python based Quant Finance Models, Tools and Algorithmic Decision Making

Jupyter Notebooks Collection for Learning Time Series Models

Predictive algorithm for forecasting the mexican stock exchange. Machine Learning approach to forecast price and Indicator behaviours of MACD, Bollinger and SuperTrend strategy

Personal Financial Forecasting Model

ALGORITHM TRADING AND STOCK PREDICTION USING MACHINE LEARNING

COVID-19 Growth Forecast

Forecasting Monthly Sales of French Champagne - Perrin Freres

This MVP data web app uses the Streamlit framework and Facebook's Prophet forecasting package to generate a dynamic forecast from your own data.

Hydrology and Climate Forecasting R package

The repository provides an in-depth analysis and forecast of a time series dataset and summarizes the mathematical concepts required to have a deeper understanding of Holt-Winter's model. Also contains the implementation and analysis to time series anomaly detection using brutlag algorithm.

Finite-Interval Forecasting Engine: Machine learning models for discrete-time survival analysis and multivariate time series forecasting

Fully Functional Point of Sale (POS) CLI system with sales, predictive and analytics tool. Written in pure C language

Beer national sales forecasting

Code accompanying the Anatolyev, S. and Baruník, J., (2019). Forecasting dynamic return distributions based on ordered binary choice. International Journal of Forecasting, 35(3), pp.823-835

This code finds the best algorithm from sklearn to forecast your numeric data

Runs streamflow forecasts using ECMWF predicted runoff and RAPID (Forked from: https://github.com/CI-WATER/erfp_data_process_ubuntu_aws).

A comprehensive suite of surf forecasting and wave analysis tools

Forecasting future traffic to Wikipedia pages using AR MA ARIMA : Removing trend and seasonality with decomposition

[Sklearn] [Python] [SQL] Machine Learning project - forecasting company sales finish with pipeline data