TSF-GRIP

Internship Tasks for Nov 21 along with instructions and final links

Internship-Tasks

This is one of the tasks given to us in the internship we are doing with The Sparks Foundation Graduate Rotational Internship Program

Task 1

Prediction using Supervised ML

● Predicting students percentage based on the number of hours studied.

● What will be the score if a student studied for approx 9.25 hrs/ day ?

● Solving this problem with a linear regression model which involves 2 variables.Namely Hours and Scores

http://bit.ly/w-data

IBM

https://jp-tok.dataplatform.cloud.ibm.com/analytics/notebooks/v2/f5c71d08-3cb7-4bce-bbc0-f4a7e43298ad/view?access_token=4ff1e7b464e8f2ca9328e270d0b47254ecef3b4d423ffb18ba2ce6ae44086056

Gist

https://gist.github.com/Abish4i/ae92c4817381516095f1d1909c5d175b

Task 2

Prediction using Unsupervised ML on Iris Dataset

● Predicting optimum number of clusters and representing them.

● Iris dataset from sklearn datasets

● Using K-Means and WCSS for predicting clusters

http://bit.ly/3kXTdox

IBM

https://jp-tok.dataplatform.cloud.ibm.com/analytics/notebooks/v2/b26d6678-5144-4989-81a8-886b2de097c3/view?access_token=4351cdb96e33b78e5fcadf021c5ec2ee4179e7a89c9e60911033dacd15aeb709

Gist

https://gist.github.com/Abish4i/9551cffe281c35704834cff172399fd6

Task 3

Exploratory Data Analysis

● 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?

https://bit.ly/3i4rbWl

Task 4

Exploratory Data Analysis-Terrorism

● Perform ‘Exploratory Data Analysis’ on dataset ‘Global Terrorism’

● As a security/defense analyst, try to find out the hot zone of terrorism.

● What all security issues and insights you can derive by EDA?

https://bit.ly/2TK5Xn5

Task 5

Exploratory Data Analysis - Sports

● Perform ‘Exploratory Data Analysis’ on dataset ‘Indian Premier League’

● As a sports analysts, find out the most successful teams, players and factors contributing win or loss of a team.

● Suggest teams or players a company should endorse for its products.

https://bit.ly/34SRn3b

Task 6

Prediction using Decision Tree Algorithm

● 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.

https://bit.ly/3kXTdox

Task 7

Stock Market Prediction using Numerical and Textual Analysis

● Objective: Create a hybrid model for stock price/performance prediction using numerical analysis of historical stock prices, and sentimental analysis of news headlines

● Stock to analyze and predict - SENSEX (S&P BSE SENSEX)

● Download historical stock prices from finance.yahoo.com

Download textual (news) data from https://bit.ly/36fFPI6

Task 8

Timeline Analysis : Covid-19

● Create a storyboard showing spread of Covid-19 cases in your country or any region (Asia, Europe, BRICS etc) using Tableau, Power BI or SAP

● Use animation, timeline and annotations to create attractive and interactive dashboards and story

● Identify interesting patterns and possible reasons helping Covid-19 spread with basic as well as advanced charts

● Screen-record the completed storyboard along with your audio explaining the charts and giving recommendations.

Updated .csv file at https://bit.ly/30d2gdi