A comprehensive collection of machine learning projects, tutorials, and implementations using Python and popular ML libraries.
This repository is perfect for anyone looking to dive into machine learning fundamentals, experiment with models, and build hands-on experience.
- Supervised Learning: Implementations of regression, classification algorithms.
- Unsupervised Learning: Clustering, dimensionality reduction techniques.
- Deep Learning: Neural networks and related projects.
- Datasets & Notebooks: Sample datasets and Jupyter notebooks for easy experimentation.
- Utilities: Helper scripts for data preprocessing, visualization, and evaluation.
git clone https://github.com/udaykiriti/machine-learning.git
cd machine-learning
# Start exploring notebooks or run Python scripts
jupyter notebook
- Python 3.7+
- Popular ML libraries like
scikit-learn,tensorflow,pandas,numpy - Jupyter Notebook (optional but recommended)
Run notebooks or scripts to train models, evaluate results, or visualize data. Modify and experiment with parameters to deepen your understanding.
Some projects include tests or example runs. Use the following to run tests where applicable:
pytest
Contributions are highly welcome! Share your machine learning projects, improvements, or bug fixes by forking the repo and submitting pull requests.

