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My Streamlit App Explore ML Models on Popular Datasets

Welcome to my interactive Machine Learning Model Explorer built using Streamlit. This app allows users to:

  • Select different datasets
  • Choose between popular ML models (SVM, KNN, Random Forest)
  • Tune hyperparameters through the sidebar
  • Visualize results in 2D using PCA
  • View model accuracy scores instantly

Features

Select from popular datasets:

  • Iris
  • Breast Cancer
  • Wine

Choose and tune classifiers:

  • K-Nearest Neighbors (KNN) – Adjust the number of neighbors
  • Support Vector Machine (SVM) – Control the regularization parameter C
  • Random Forest – Set n_estimators and max_depth

Real-time insights:

  • Shows dataset shape and number of classes
  • Displays accuracy of the selected model
  • Visualizes data in 2D using PCA with color-coded target labels

Tech Stack

  • Python
  • Streamlit
  • Scikit-learn
  • Matplotlib
  • NumPy

App Preview

App Screenshot

How to Run This App Locally

# 1. Clone the repository
git clone https://github.com/YourUsername/My-Streamlit-App.git

# 2. Navigate into the project directory
cd My-Streamlit-App

# 3. Install the dependencies
pip install -r requirements.txt

# 4. Run the Streamlit app
streamlit run app.py