Streamlit-webapps

Basic-ml: Simple streamlit visualization app

Different sklearn toy-datasets like Iris dataset, Breast cancer dataset & Wine dataset are vizualized graphically using matplotlib library in the streamlit app. The datasets are classified with different supervised ML classifiers like KNN, SVM & Random Forests.
Shape of the dataset, no. of classes along with its accuracy score for particular classifier are displayed above the graph. There is also a sidebar to tweak certain parameters related to the different classifiers used.

Sklearn's generated datasets

This app is used to check the influence of various parameters/arguments on the sample data points of generated datasets.
Variuos generated datasets include: make_moons, make_circles & make_classification which creates two interleaving data points for classification purposes.
Used to visualize clustering and classification algorithms.

Linear SVM classifier in action

To check real-time implementation of Linear SVM classifier using polynomial features on the sklearn generated dataset: make_moons.

Daily Defects app

Web-app to track daily defects in producion-level for QA.
Mobile-friendly view of the web based app.
PDF download section also available for download of detailed defect report.

Web-view

Mobile-view