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

---

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