GRIP: The Sparks Foundation Data Science and Business Analytics Intern TASK 1: Prediction using Unsupervised ML Problem Statement: Predict the percentage of an student based on the no. of study hours. Tool Used: Python (Google Colab) Dataset used: http://bit.ly/w-data Prediciton using Linear regression

GRIP : The Spark Foundation ( Data Science and Business Analytics Intern ) Author :Dhivya S Prediction using Supervised ML (Level - Beginner) ● Predict the percentage of an student based on the no. of study hours. ● This is a simple linear regression task as it involves just 2 variables. ● You can use R, Python, SAS Enterprise Miner or any other tool ● Data can be found at http://bit.ly/w-data ● What will be predicted score if a student studies for 9.25 hrs/ day? ● Sample Solution : https://bit.ly/2HxiGGJ Supervised machine learningis a type of machine learning in which the machine is fed the training data which is labelled. Supervised machine learning is further categorized into regression and classification Linear regression is probably the simplest approach for statistical learning. It is a good starting point for more advanced approaches, and in fact, many fancy statistical learning techniques can be seen as an extension of linear regression. Therefore, understanding this simple model will build a good base before moving on to more complex approaches.Output type- continuous (number)

Task1 The Spark Foundation

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This repository is the first task of the web-development internship by The Sparks Foundation.

Task 1 : Prediction using Supervised Machine Learning

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Hello everyone this is my #task1 submission for TSF Web Development and Design Intern October 2023. #thesparksfoundation #internship #griptask #sparks_foundation #GRIPOCT23 #GRIPOCTOBER23 #grip #webdevelopment

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Prediction using Supervised ML

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Supervised Machine Learning with Linear Regression.

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The Spark Foundation Task1 Prediction Using Supervised ML (Data Science And Business Analytics Intern)

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Web and Mobile Development/Basic Banking System Project