SPARKS-FOUNDATION

This repository contain all the task given in the sparks foundation internship program Data Science & Business Analytics Tasks

TASK 1

Prediction using Supervised ML

Level - Beginner

Predict the percentage of an student based on the no. of study hours. This is a simple linear regression task as it involves just 2 variables. You can use R, Python, SAS Enterprise Miner or any other tool Data can be found at http://bit.ly/w-data What will be predicted score if a student studies for 9.25 hrs/ day? Sample Solution : https://bit.ly/2HxiGGJ Task submission: Host the code on GitHub Repository (public). Record the code and output in a video. Post the video on YouTube Share links of code (GitHub) and video (YouTube) as a post on YOUR LinkedIn profile, not TSF Network. Submit the LinkedIn link in Task Submission Form when shared.

TASK 2

Prediction using Unsupervised ML

Level - Beginner

From the given ‘Iris’ dataset, predict the optimum number of clusters and represent it visually. Use R or Python or perform this task Dataset : https://bit.ly/3kXTdox Sample Solution : https://bit.ly/3cGyP8j Task submission: Host the code on GitHub Repository (public). Record the code and output in a video. Post the video on YouTube Share links of code (GitHub) and video (YouTube) as a post on YOUR LinkedIn profile Submit the LinkedIn link in Task Submission Form when shared. Please read FAǪs on how to submit the tasks.

Task 3

Exploratory Data Analysis - Retail

(Level - Beginner) ● Perform ‘Exploratory Data Analysis’ on dataset ‘SampleSuperstore’ ● As a business manager, try to find out the weak areas where you can work to make more profit. ● What all business problems you can derive by exploring the data? ● You can choose any of the tool of your choice (Python/R/Tableau/PowerBI/Excel/SAP/SAS) ● Dataset: https://bit.ly/3i4rbWl ● Beginner Level - Create dashboards. Screen-record along with your audio explaining the charts and interpretations. ● Task submission:

1. Create the dashboards and/or storyboard and record it
2. Upload the recording either on YouTube or LinkedIn
3. Create a LinkedIn post as suggested in FAQs

##Task 6 ###Prediction using Decision Tree Algorithm (Level - Intermediate) ● Create the Decision Tree classifier and visualize it graphically. ● The purpose is if we feed any new data to this classifier, it would be able to predict the right class accordingly. ● Dataset : https://bit.ly/3kXTdox ● Sample Solution : https://bit.ly/2G6sYx9 ● Task submission:

1. Host the code on GitHub Repository (public). Record the code and output in a video. Post the video on YouTube
2. Share links of code (GitHub) and video (YouTube) as a post on YOUR LinkedIn profile
3. Submit the LinkedIn link in Task Submission Form when shared.
4. Please read FAQs on how to submit the tasks.