This project provides implementations of some deep learning algorithms for Multivariate Time Series Forecasting
- Transformers
- Recurrent neural networks (LSTM and GRU)
- Convolutional neural networks
- Multi-head multi-layer perceptron
Prequisites are defined in requirements.txt file
A running example is implemented in _main_.py
Used Dataset is not included in this project
A Jupyter notebook for RNN model is also available.
The used open dataset 'Household Power Consumption' available at https://archive.ics.uci.edu/ml/datasets/individual+household+electric+power+consumption
Prep-processing steps to get the used cleaned version are available in the tutorial https://machinelearningmastery.com/multi-step-time-series-forecasting-with-machine-learning-models-for-household-electricity-consumption/
React
Typescript
Django
Laravel
Facebook
Microsoft
Google
Alibaba
D3
Tencent