Machine Learning Loot Crate 💻🧰

🔴 Welcome contributors!

As we all know the BGMI Loot Crate comes with so many resources for the gamers, this ML Crate will be the hub of various ML projects which will be the resources for the ML enthusiasts!

Structure of the Projects 📝

This repository consists of various machine learning projects, and all of the projects must follow a certain template. I wish the contributors will take care of this while contributing in this repository.

Dataset - This folder stores the dataset used in this project. If the Dataset is not being able to uploaded in this folder due to the large size, then put a README.md file inside the Dataset folder and put the link of the collected dataset in it. That'll work!

Images - This folder is used to store the images generated during the data analysis, data visualization, data segmentation of the project.

Model - This folder would have your project file (that is .ipynb file) be it analysis or prediction. Other than project file, it should also have a 'README.md' using this template and 'requirements.txt' file which would be enclosed with all needed add-ons and libraries that are included in the project.

🧮 Workflow

Fork the repository
Clone your forked repository using terminal or gitbash.
Make changes to the cloned repository
Add, Commit and Push
Then in Github, in your cloned repository find the option to make a pull request

❄️Open Source Programs!

_{Script Winter of Code 2021}

Serial No.	Project Name	Goal of the Project	Link
01	Credit Card Fraud Detection	The main aim of the project is to make a model that helps to predict credit card fraud based on the given dataset.	Click Here
02	MNIST Dataset Classification	Implement a machine learning classification algorithm on image to recognize handwritten digits from a paper.	Click Here
03	Character Recognition	Implement character recognition in natural languages. Character recognition is the process of automatically identifying characters from written papers or printed texts.	Click Here
04	Height and Weight Prediction	Build a predictive model for determining height or weight of a person. Implement a linear regression model that will be used for predicting height or weight.	Click Here
05	Fake News Detection	Build a fake news detection model with Passive Aggressive Classifier algorithm. The Passive Aggressive algorithm can classify massive streams of data, it can be implemented quickly.	Click Here