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SabraHsb/ML_DL_Algorithms_Explorer

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App README

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🤖 ML Explorer

An all-in-one interactive playground for Machine Learning algorithms

![Python](https://python.org) ![Streamlit](https://streamlit.io) ![scikit-learn](https://scikit-learn.org) ![License: MIT](LICENSE)

🚀 Live Demo on Hugging Face &nbsp;|&nbsp; 📦 GitHub Repo

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🧭 What's Inside

AlgorithmTypeKey Features
⚡ SVMClassificationKernel trick, margin visualization, support vectors
📈 RegressionRegressionLinear, Polynomial, Ridge, Lasso, residual plots
🌳 Decision Tree / RFClassificationDepth control, feature importance, ensemble power
🔵 K-MeansClustering (Unsupervised)Elbow curve, centroid animation, cluster explorer
👥 KNNClassificationK sweep, distance metrics, boundary visualization
🧠 Neural Network (MLP)ClassificationCustom architecture, loss curve, network diagram

✨ Features

  • —📂 Upload your own CSV — pick feature columns and label column interactively
  • —📦 Built-in datasets — Moons, Circles, Blobs, Iris, and more
  • —🎛️ Live hyperparameter tuning — every parameter updates the plot in real time
  • —📊 Full evaluation — confusion matrix, classification report, R² / RMSE for regression
  • —🎨 Navy dark theme — clean, professional UI throughout

🚀 Run Locally

bash
git clone https://github.com/YOUR_USERNAME/ml-explorer.git
cd ml-explorer
pip install -r requirements.txt
streamlit run app.py

Opens at http://localhost:8501 🎉

☁️ Deploy to Hugging Face Spaces

One-click via GitHub import:

  1. 1.huggingface.co/new-space → SDK: Streamlit
  2. 2.Click Import from GitHub → paste your repo URL
  3. 3.Create Space ✅

📂 CSV Upload Format

Any CSV with numeric columns works. Example:

sepal_length, sepal_width, species
5.1, 3.5, 0
4.9, 3.0, 1
...
  • —Pick Feature 1, Feature 2, and Label column in the UI
  • —Label must be binary or multi-class integers
  • —For regression: pick one feature (X) and one target (Y)

📁 Project Structure

ml-explorer/
├── app.py            # Single-file Streamlit app (~600 lines)
├── requirements.txt  # Dependencies
└── README.md         # This file

📦 Dependencies

streamlit>=1.28.0
numpy>=1.24.0
matplotlib>=3.7.0
scikit-learn>=1.3.0
pandas>=2.0.0
seaborn>=0.12.0

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Made with ❤️ using Streamlit & scikit-learn

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