/Forecasting_models_using_recurrent_neural_networks

This repository contains code for stock and temperature prediction models using RNN implemented in PyTorch.

Primary LanguageJupyter NotebookMIT LicenseMIT

Forecasting_models_using_recurrent_neural_networks.

This repository contains code for stock and temperature prediction models using RNN implemented in PyTorch. The projects are separated by folders, with the name of the datasets.

Contents

.
├── imgs
│   ├── acoescf.png
│   ├── acoes.png
│   └── pol.png
├── LICENSE
├── README.md
├── requirements.txt
└── RNN_models
    ├── Modelo_de_série_temporal_da_poluição_na_China.ipynb
    ├── Previsão_do_preço_de_ações_com_redes_neurais_recorrentes.ipynb
    ├── Previsão_do_preço_de_ações_com_redes_neurais_recorrentes_múltiplas_saídas.ipynb
    └── Previsão_do_preço_de_ações_com_redes_neurais_recorrentes_múltiplos_previsores.ipynb

The RNN_models folder contains the python codes used in projects.The other folders follow the same pattern.

Requirements

  • Check the requirements.txt file.

Test

git clone https://github.com/gslmota/Forecasting_models_using_recurrent_neural_networks.git
cd Forecasting_models_using_recurrent_neural_networks
pip install -r requirements.txt

Results

RNN stock value predictor:

  • Rnn. This project using a RNN model.

!RNN

RNN open and bullish value predictor:

  • Rnn. This project using a RNN model.

!RNN

RNN pollution forecaster:

  • Rnn. This project using a RNN model.

!RNN

References: