Machine Learning Webapp Deployed Using Streamlit

A machine learning application which lets you compare different machine learning algorithms and tune parameters with interactive GUI. This was achieved using streamlit. Streamlit is an open-source Python library that makes it easy to build beautiful custom web-apps for machine learning and data science.

This application lets you play around with different machine learning algorithms:-

1. K Nearest Neighbors
2. Support Vector Classifier
3. Random Forest

You can also change the datasets:-

1. Iris Dataset
2. Breast Cancer Dataset
3. Wine Quality Dataset

I also display the datapoints plotted on a 2-D plane by decomposition using Principle Component Analysis. There is an option for scaling the data as well.

Tech Stack

1. Stremlit
2. sk-learn
3. PCA

How to Run

1. Clone this repository on your local machine
2. Install Streamlit: pip install streamlit
3. Run the Streamlit app using: streamlit run app.py

Preview

App look with KNN algorithm and Iris Dataset

Wine Quality dataset with Random Forest and Scaled Data