/Sparks-Foundation

Data Science & Business Analytics intern and secured a bronze hand Graduate Rotational Internship Program (GRIP), offered by The Sparks Foundation

Primary LanguageJupyter NotebookGNU General Public License v3.0GPL-3.0

The Sparks Foundation Tasks

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

  • Internship Category - Data Science and Business Analytics

# 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 https://raw.githubusercontent.com/AdiPersonalWorks/Random/master/student_scores%20-%20student_scores.csv
  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 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

# Task-3 : Exploratory Data Analysis - Retail (Level - Beginner)

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

  1. Find out the weak areas in a business, where you can work to make more profit. Find the various business problems which can be derived by exploring the data.
  2. Data can be found at https://drive.google.com/file/d/1lV7is1B566UQPYzzY8R2ZmOritTW299S/view

# Task-4 : 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-5 : Exploratory Data Analysis - Sports (Level - Advanced)

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

  1. Problem Statement: Perform Exploratory Data Analysis on 'Indian Premiere League'
  2. As a sports analysts, find out the most successful teams, players and factors contributing win or loss of a team.
  3. Suggest teams or players a company should endorse for its products.
  4. Data can be found at https://bit.ly/34SRn3b

# Task-6 : Exploratory Data Analysis - Terrorism (Level - Intermediate)

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

  1. Perform ‘Exploratory Data Analysis’ on dataset ‘Global Terrorism’
  2. As a security/defense analyst, try to find out the hot zone of terrorism.
  3. What all security issues and insights you can derive by EDA?
  4. Data can be found at https://bit.ly/2TK5Xn5