The Spark 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 ( August - 2021 )
• Internship Type - Work from Home

In this internship, we were provided a total of 10 Tasks (6 from own domain and 2 from other domains) and I was able to successfully complete all the 8 tasks within the given time-frame.

(Task 1 - Linear_Regression.ipynb)

#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

#Task-4 : Stock Market Prediction using Numerical and Textual Analysis (Level - Advanced)

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

NOTE : If you face any issue over dataset then please refer to the thread of Issue #2.

1. Create a hybrid model for stock price/performance prediction using numerical analysis of historical stock prices, and sentimental analysis of news headlines.
2. Stock to analyze and predict SENSEX (S&P BSE SENSEX)
3. Download historical stock prices from finance.yahoo.com
4. Download textual (news) data from https://bit.ly/36fFPI6
5. Use either R or Python, or both for separate analysis and then combine the findings to create a hybrid model.

#Task-5 : To Explore Business Analytics (Level - Beginner & Intermediate)

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

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

#Task-6 : Timeline Analysis : Covid-19 (Level - Advanced)

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

1. Create a storyboard showing spread of Covid 19 cases in your country or any region (Asia, Europe, BRICS etc)
2. Use animation, timeline and annotations to create attractive and interactive dashboards and story
3. Identify interesting patterns and possible reasons helping Covid 19 spread with basic as well as advanced charts
4. Use Tableau or Power BI for this task
5. Screen record the completed storyboard along with your audio explaining the charts and giving recommendations.
6. Dataset: Daily updated .csv file on https://bit.ly/30d2gdi

References -

• Tableau
• Scikit learn