Coding exercise using machine learning to forecast GB hourly day-ahead electricity prices for 2020
Possible approaches:
- ARIMA models
- Regression (linear, XGBoost, Random Forest)
- Deep learning (RNN, LSTM)
Final approach:
- Linear regression
- The code was written in a Google Colab Notebook (compatible with Jupyter Notebook).
NG_EPF_exercise.ipynb - this script processes the data and runs the models. It also contains the responses to the questions.
predicted_prices_2020_linear_reg.csv - this is the output file.
Fem Alonge
This project is licensed under the MIT License - see the LICENSE.md file for details