This repository contains the tasks completed during my GRIP (Graduate Rotational Internship Program) internship. Below is a detailed description of each task.
Predict the percentage score of a student based on the number of study hours.
This is a simple linear regression task involving two variables: the number of study hours and the percentage score.
Predicted score for a student studying 9.25 hours/day: 94.80
Predict the optimum number of clusters in the Iris dataset and represent it visually.
Use the Iris dataset to perform clustering and determine the optimal number of clusters.
Optimal number of clusters: 3
Visualization:
Perform Exploratory Data Analysis (EDA) on the 'Superstore' dataset to identify weak areas and potential business problems.
Analyze the 'Superstore' dataset to derive insights that can help improve business profitability.
