Repository to study ML.
Regression task, from the book "Hands on Machine Learning", to predict the median house price values of thousands of districts from the state of California, USA 1990.
The dataset was acquired from the author of the book: raw.githubusercontent.com/ageron/handson-ml/master/datasets/housing/housing.tgz
The code is located on machine_learning_projects/housing_project/code/housing_data.py
Regression task to predict the protein values of thousands of food items based on major food nutrient values: carbohydrate, energy, water, fat and nitrogen.
The datasets were acquired from the U.S Department of Agriculture: fdc.nal.usda.gov/download-datasets
The code is located on machine_learning_projects/food_project/code/food_project.py
- Python
- Packages: matplotlib, numpy, pandas, scipy, scikit-learn, joblib
git clone https://github.com/weslleyskah/machine_learning_projects.git
cd machine_learning_projects# Create a virtual environment
uv venv
# Install packages
uv pip install -r requirements.txtcd housing_project/code
uv run housing_data.py| Folder | Description |
|---|---|
| datasets/ | Contains source and reshaped .csv files from the datasets |
| datasets_src/ | Local dataset files |
| food_project/ | Food dataset analysis using U.S. Department of Agriculture data |
| housing_project/ | Housing project from "Hands-On Machine Learning" by Aurélien Géron |
| img/ | Visualization images generated using matplotlib |
| models/ | Trained machine learning models |
| venv/ | Python virtual environment for dependency management |
| requirements.txt | Python packages |
| .gitignore | Files and folders to be ignored |
| README.md | Notes |