GRIP -The Spark Foundation

The Sparks Foundation - Graduation Rotational Internship Program

This Repository is dedicated to the completion of my Task with video from The Sparks Foundation (Graduate Rotational Internship Program).
My domain is Data Science and Business Analytics for the May 2024 Batch.

Tools/IDE : Python/Jupyter Notebook

TASK - 1 :- Prediction using Supervised ML (Level - Beginner) (Simple Linear Regression)

Predict the percentage of marks that a student is expected to score based upon the number of hours they studied

dataset- http://bit.ly/w-data

https://github.com/praggatii/The_Spark_Foundation-Internship2024

Requirementes

• pandas - numpy - matplotlib - seaborn - sklearn

Predicted Score for 9.25 hours: 93.69173248737539 percent

TASK 6 :- Prediction using Decision Tree Algorithm (Level - Intermediate)

• Task Description: In this task, we will Create the Decision Tree classifier and visualize it graphically on the dataset "Iris" and try to find out if we feed any new data to this classifier, it would be able to predict the right class accordingly.
• Dataset: Iris Dataset
• Dataset Link: https://bit.ly/3kXTdox
• Tech Stack: scikit-learn, seaborn
• Task Video: