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Devs-Machine-Learning-Playground

This repository contains different Machine Learning, Deep Learning, and Data Analysis Projects. If you worked on some good projects and want to share it with the world, you can do that through us and join our valued sea of contributers.

Look how you can contribute here Contribution Guidelines.

Projects

S.No Project Name Description
1 Automatic License Number Plate Recognition System To detect and recognize the license number plate of a vehicle and read the license numbers printed on the plate
2 Dogecoin Price Predictor Predict the price of the Dogecoin using previous data
3 Emojify Create your own emoji with Python
4 Online Grocery Recommendation using Collaborative Filtering Project to make customers realize what they would like in their baskets
5 Orange Fruit Recognition Detecting whether the fruit shown is Orange or Not Using Image Segmentation
6 Personality Predictor Identify the personality of a person from the type of posts they put on social media
7 Sign Language Recognition Create a sign detector that detects sign language
8 Speech Emotion Recognition It takes a part of speech as input and then determines in what emotions the speaker is speaking
9 Uber Data Analysis Perform data visualization on the uber data
10 Wine Quality Test Build a Model to predict the quality of the red wine
11 Xbox Game Predictor Data generated by people while searching can be used to predict the interest of the users


Contribution Guidelines ⚙️

You may go through these guidelines and contribute accordingly:

  • Make sure you do not copy codes from external sources like GFG, hackerearth, etc because that work will not be considered. Plagiarism is strictly not allowed.
  • You can only work on issues that you have been assigned to you.
  • If you want to contribute for an existing algorithm, we prefer that you create an issue before making a PR and link your PR to that issue.
  • If you have modified/added code work, make sure the code compiles before submitting.
  • Strictly use snake_case (underscore_separated) in your file_name and push it in correct folder.
  • Just mention the issue against which the pull request is open by writing Fixes #(your issue number) in the description of the pull request
  • Do not update the README.md.
  • Do not push any changes in the main branch. Always make a new branch with the number assosiated with you issue.
  • Refer Devs-Git-Cheatsheet in order to learn how to create new branch, fix any error etc.
  • If you are a beginner and have no idea how to contribute to opensource projects then see Steps-for-beginners.


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This repository contains different Machine Learning, Deep Learning, and Data Analysis Projects.

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