The-Sparks-Foundation-Tasks

This repository contains the tasks that I completed while working as an intern for The Sparks Foundation.

• Internship Category - Data Science and Business Analytics
• Internship Duration - 1 Month ( July-2021 )
• Internship Type - Work from Home

In this internship, we were provided a total of 6 Tasks and I was able to successfully complete all the 6 tasks within the given time-frame.

# Task-1 : Prediction using Supervised ML (Level - Beginner)

Please click on the images on right side to view my solution.

1. Predict the percentage of marks of an student based on the number of study hours.
2. This is a simple linear regression task as it involves just 2 variables.
3. Data can be found at http://bit.ly/w
4. You can use R, Python, SAS Enterprise Miner or any other tool.
5. What will be predicted score if a student studies for 9.25 hrs/ day?

# Task-2 : Prediction using Unsupervised ML (Level - Beginner)

Please click on the images on right side to view my solution.

1. From the given ‘Iris’ dataset, predict the optimum number of clusters and represent it visually.
2. Use R or Python or perform this task.
3. Data can be found at https://bit.ly/3cGyP8j

# Task-3 : Prediction using Decision Tree Algorithm(Level - Intermediate)

Please click on the images on right side to view my solution.

1. For the given ‘Iris’ dataset, create the Decision Tree classifier and visualize it graphically.
2. The purpose is if we feed any new data to this classifier, it would be able to predict the right class accordingly.
3. Data can be found at https://bit.ly/3kXTdox

References -

• Tableau
• Scikit Learn