Data_processing.ipynb Data Science
▸ src/notebooks/Data_processing/ (cleaning)
▸ src/notebooks/sarimax_model/ (statistical forecast)
▸ src/notebooks/XGBoost Model/ (boosting model)
▸ src/utils/ (metrics + plotting)
Master TFM: Advanced Time-Series Analysis
Python 3.11 Jupyter Notebook Poetry Data Science Time-Series Forecasting Machine Learning Deep Learning Pandas NumPy scikit-learn TensorFlow Keras XGBoost SARIMAX Statsmodels Matplotlib Seaborn PMDARIMA Ruff
Master's final thesis project focused on energy demand forecasting with the Open Power System Data 60-minute dataset. This is not a web app: it's a notebook-first data science workspace (99%+ Jupyter) organized in `src/notebooks` (Data_processing, SARIMAX, XGBoost, CNN, LSTM), `src/utils` (data loading, plotting, conclusion metrics), and `src/datasets`. The project uses Poetry for reproducible dependency management, includes cross-platform initialization scripts (`initialize.py/.sh/.ps1/.cmd`) for dataset bootstrap, and compares statistical + ML/DL approaches with Python 3.11, pandas, NumPy, scikit-learn, TensorFlow/Keras, statsmodels, and pmdarima.