skforecast
Time series forecasting with machine learning models
pmdarima
A statistical library designed to fill the void in Python's time series analysis capabilities, including the equivalent of R's auto.arima function.
synthpred
A Julia package for synthetic data analysis, advanced imputation (ARIMA, RNN), AutoML, and ensemble modeling.
https://github.com/biolab/orange3-timeseries
🍊 :chart_with_upwards_trend: Orange add-on for analyzing, visualizing, manipulating, and forecasting time series data.
runhic
An easy-to-use Hi-C data processing software supporting distributed computation.
https://github.com/business-science/modeltime
Modeltime unlocks time series forecast models and machine learning in one framework
load_forecasting
Forecasting electric power load of Delhi using ARIMA, RNN, LSTM, and GRU models
https://github.com/nixtla/statsforecast
Lightning ⚡️ fast forecasting with statistical and econometric models.
https://github.com/adamouization/solar-irradiance-forecasting
Predicting short-term solar irradiance using deep learning and statistical methods on the Folsom dataset
tsa-course
Book and material for the course "Time series analysis with Python" (STA-2003)
stock-market-prediction-web-app-using-machine-learning-and-sentiment-analysis
Stock Market Prediction Web App based on Machine Learning and Sentiment Analysis of Tweets (API keys included in code). The front end of the Web App is based on Flask and Wordpress. The App forecasts stock prices of the next seven days for any given stock under NASDAQ or NSE as input by the user. Predictions are made using three algorithms: ARIMA, LSTM, Linear Regression. The Web App combines the predicted prices of the next seven days with the sentiment analysis of tweets to give recommendation whether the price is going to rise or fall
https://github.com/aarjaneiro/cronoseries
A fork of Cronos with a focus on being a Time Series class library.