Code Monkey home page Code Monkey logo

tsf-supervised-machine-learning's Introduction

THE SPARKS FOUNDATION - SUPERVISED MACHINE LEARNING

TSF - SUPERVISED MACHINE LEARNING TASK - 1


  • Task: To predict the percentage of a student based on the number of study hours.

    • Simple Linear Regression is used as it involves just 2 variables.

    • Output: To find predicted score if a student studies for 9.25 hrs/day.

TECHNOLOGIES AND LIBRARIES USED:

  • Python3, Pandas, Numpy, Matplotlib.pyplot, Seaborn.

๐Ÿ‘‰๐Ÿป Presented as a part of the Internship @ The Sparks Foundation ๐Ÿ‘ˆ๐Ÿป

โœŒ๐Ÿป Back To Engineering โœŒ๐Ÿป

tsf-supervised-machine-learning's People

Contributors

amey-thakur avatar

Stargazers

 avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar

Watchers

 avatar  avatar

Recommend Projects

  • React photo React

    A declarative, efficient, and flexible JavaScript library for building user interfaces.

  • Vue.js photo Vue.js

    ๐Ÿ–– Vue.js is a progressive, incrementally-adoptable JavaScript framework for building UI on the web.

  • Typescript photo Typescript

    TypeScript is a superset of JavaScript that compiles to clean JavaScript output.

  • TensorFlow photo TensorFlow

    An Open Source Machine Learning Framework for Everyone

  • Django photo Django

    The Web framework for perfectionists with deadlines.

  • D3 photo D3

    Bring data to life with SVG, Canvas and HTML. ๐Ÿ“Š๐Ÿ“ˆ๐ŸŽ‰

Recommend Topics

  • javascript

    JavaScript (JS) is a lightweight interpreted programming language with first-class functions.

  • web

    Some thing interesting about web. New door for the world.

  • server

    A server is a program made to process requests and deliver data to clients.

  • Machine learning

    Machine learning is a way of modeling and interpreting data that allows a piece of software to respond intelligently.

  • Game

    Some thing interesting about game, make everyone happy.

Recommend Org

  • Facebook photo Facebook

    We are working to build community through open source technology. NB: members must have two-factor auth.

  • Microsoft photo Microsoft

    Open source projects and samples from Microsoft.

  • Google photo Google

    Google โค๏ธ Open Source for everyone.

  • D3 photo D3

    Data-Driven Documents codes.