This repo contains machine learning models for time series data forecasting which includes:
The single output-multi-step forecast
The multi-output-single-step forecast
And single-output-single-step forecast
The traditional machine learning models used for forecasts (multi and single step forecasts) are:
Random forest, SVM and Linear regression
The deep learning neural networks used for forecasts (multi and single step forecasts) are:
ANN, CNN, GRU and LSTM
The airplane passengers - https://www.kaggle.com/datasets/chirag19/air-passengers and human activity recognition (HAR) - https://www.kaggle.com/datasets/meetnagadia/human-action-recognition-har-dataset datasets were used.
