A collection of data science and machine learning notebooks covering insurance, weather prediction, housing prices, outbreak analysis, and sales forecasting.
AcemClaimInsuranceIncorp.ipynb— standalone insurance notebook at the root.AcmeInsurance/— insurance-related notebook and dataset.AustraliaWeatherPrediction/— weather prediction notebooks, including logistic regression and random forest examples.HousingPrices/— notebooks for housing price exploration, feature engineering, and model development.MLOPS/— placeholder folder for MLOps-related work.Outbreaks/— outbreak data analysis notebooks and CSV data.Statistical Technique/— notebooks for categorical correlation, feature selection, missing value imputation, and statistical experiments.StoreSales/— sales forecasting notebook.
- Open the repository in VS Code or Jupyter.
- Launch Jupyter Notebook or JupyterLab.
- Open the notebook you want to explore.
- Run cells sequentially to reproduce the analyses.
- Datasets are stored alongside the notebooks in their respective folders.
- Some notebooks may require installation of standard Python data science libraries such as
pandas,numpy,scikit-learn, andmatplotlib.