ai-friday-tsf-xai/README.md

Time series forecasting energy prices

With features representing energy generation of various sources (oil/biomass/hydro)

Setup

Prerequisites:

• Have a working version of pip preferably in Python 3.12

Steps

1. Install uv

pip install uv

2. Create & activate virtual environment

uv venv .venv
# on Windows
.\.venv\Scripts\activate
# on Linux:
source .venv/bin/activate

3. Install the dependencies

uv pip install .

Get hackin'

Look in tsforecast.ipynb

• Play around with some of the techniques
  • Seasonal decompose
  • SARIMA
  • XGBoost
  • LSTM
• Try to beat my MAE on test set of ~0.31 (I used LSTM)