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Charitra-1 / GRIP-TASK

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Predictive Models and Clustering Visualization for GRIP-TASK Web Application #1

Closed chandankumarm55 closed 1 week ago

chandankumarm55 commented 2 weeks ago

Description: I would like to enhance the current GRIP-TASK web application by adding two new features that focus on predictive analytics and data clustering visualization.

Task 1: Predict the percentage of a student based on the number of study hours. This task will involve implementing a linear regression model that estimates a student's percentage score based on their study hours.

Task 2: Predict the optimum number of clusters in the Iris dataset using clustering algorithms like K-means and visualize the results. This task will involve preprocessing the Iris dataset, applying the clustering model, and visualizing the clusters.

Screenshot 2024-08-25 120333

Proposed Solution: To implement these enhancements, I suggest using the following technologies:

Streamlit: To create an intuitive and interactive web interface for both tasks. Deployment: Deploy the updated application on Streamlit Cloud to make it easily accessible.

Request: I am keen to work on this issue and would like to contribute to the repository by implementing these tasks. Please assign this issue to me.

chandankumarm55 commented 2 weeks ago

@Charitra-1 I have tested the app locally. If necessary, you can test it as well. Please merge the PR into the main branch: PR #2.