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Estimating Student Scores Based on Study Hours Using Linear Regression

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jupyter-notebook ml prediction python regression supervised-machine-learning

academic_performance_prediction's Introduction

Prediction using Supervised ML

This is a simple regression task

The 'Prediction using Supervised ML' is a Data Science and Business Analytics Internship Project (Task #1) as part of GRIP(Graduate Rotational Internship Program)@The Sparks Foundation

This repository contains the .ipynb file using which I have executed the task.

Task Instructions

  1. Predict the percentage scored by a student based on the number of hours studied.
  2. What will be the predicted score if the student studies for 9.25 hours/day?

Tools and Languages used

  • Python
  • Colaboratory - Google Colab

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