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Tasks which I have done during the internship at GRIP-The Spark foundation

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GRIP-The-Spark-Foundation-Internship

Tasks which I have done during the internship at GRIP-The Spark foundation

Task 1 - Improve LinkedIn Profile

Watch videos and read online articles to see the best practices about improving your LinkedInProfile
Complete your LinkedIn Profile with all details from your resume, e.g. Objective, Education, Projects, Experience,etc..
Add your professors, friends, seniors, industry leaders, etc. to your connections. Send invitation request to many. This will help you get job later on.
Look at the connections of your existing network and add others who have reputed profile.
Add and follow all the members on the TSF page.
Join the TSF network and post your questions/ queries there.

LinkedIn Link: https://www.linkedin.com/in/dandapatsuman/

Task 2 - To Explore Supervised Machine Learning

In this regression task we will predict the percentage of marks that a student is expected to score based upon the number of hours they studied. This is a simple linear regression task as it involves just two variables.
Data can be found at http://bit.ly/w-data
What will be predicted score if a student study for 9.25 hrs in a day?

Task 3 - To Explore Unsupervised Machine Learning

From the given ‘Iris’ dataset, predict the optimum number of clusters and represent it visually.
Dataset : https://drive.google.com/file/d/11Iq7YvbWZbt8VXjfm06brx66b10YiwK-/view?usp=sharing

Task 4 - To Explore Decision Tree Algorithm

For the given ‘Iris’ dataset, 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://drive.google.com/file/d/11Iq7YvbWZbt8VXjfm06brx66b10YiwK-/view?usp=sharing

Task 5 - To Explore Business Analytics

Perform ‘Exploratory Data Analysis’ on the provided dataset ‘SampleSuperstore’
As the business owner of the retail firm and want to see how your company is performing. You are interested in finding out the weak areas where you can work to make more profit. What all business problems you can derive by looking into the data?
Dataset: https://drive.google.com/file/d/1lV7is1B566UQPYzzY8R2ZmOritTW299S/view

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Tasks which I have done during the internship at GRIP-The Spark foundation

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