Welcome to my collection of Machine Learning algorithms, experiments, and Jupyter notebooks. This repo is my personal playground for learning, testing, and implementing concepts in ML (and soon DL).
📂 Repository Structure
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*.ipynb → Jupyter notebooks with code + explanations.
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*.py → Python scripts for reusable functions or models.
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data/ → Sample datasets (if small enough).
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models/ → Saved trained models (future).
🧠 Current Topics
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✅ Classical ML algorithms (Linear Regression, Decision Trees, SVM, etc.)
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✅ Hands-on Jupyter notebooks for practice
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✅ Python implementations of key algorithms
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🔜 Deep Learning (Neural Networks, CNNs, RNNs, Transformers, etc.)
⚙️ Requirements
You’ll need Python (≥3.8) and some core libraries. Recommended setup:
pip install -r requirements.txt
Clone the repo:
git clone https://github.com/Suraj-035/PythonLearn.git
cd PythonLearn
🤝 Contributing Suggestions, improvements, or cool ideas? Feel free to fork and submit a PR.