ML-ProjectKart

📌Repository

This kart showcases the finest collection of all projects based on machine learning, deep learning, computer vision, natural language processing and everything. Indulge in this journey of open source.

The main aim is to provide an efficient and beginner-friendly projects that would help you in mastering the ML/AI algorithms and make you familiar. Turn yourself into pro with all the hands-on that got you covered.

🙌Join Here

Anyone related to technology who are looking to contribute to open-source, are all invited to hop in. This place has task for everyone.

Data Analysts - Frame the problem. Get, explore and prepare the data

Machine Learning, Deep Learning, Computer Vision, Natural Language Processing Enthusiasts - Try different algorithms, build model, optimize the model

Front End Designers – Design or code the webpage designed by designers

Back End Developers – Create backend for the model using Flask or Django

UI/UX Designers – Design dashboards, forms and webpages for the model

If you had worked on or want to initiate a unique project and want to share it with the world, you can do that through here. Go through the contributing guidelines in CONTRIBUTING👩‍💻

When issue is raised from your end (or) taken it from issues tab to add a project, elaborate as much as you could and as well notify us about the task you will be working, that might be Model Creation (or) Data Analysis (or) Front End (or) Back End (or) UI/UX Design.

Subsequently, also go through the GitHub documentation on creating a pull request.

🛠Templates to Follow

Note : One should follow these templates while creating a new issue or pull request. Else, 'LGM-SOC' label won't be assigned neither your contributions would count. This is to ensure that we know you as a 'LGM-SOC' participant. If you had taken up the issue, that's already in the "Issues" tab. You should mention yourself as 'LGM-SOC' participant.

📝Project Structure

Your projects should contain this flow to maintain similarity across all other projects. Make sure to note these things, before you create a PR.

Dataset - This folder would have a .csv file.

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

Images - This folder would have images added if applicable.

Front End - This folder would have files related to coding and designing the webpage.

Back End - This folder would have files regarding backend creation for the model using Flask and Django.

UI/UX - This folder would have files regarding dashboards, forms and webpages for the model.

Include README.md file for 'Front End', 'Back End' and 'UI/UX' in their respective folders and elaborate briefly about how it works by showing step by step procedure using screenshots.

👨‍💻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

print("Start contributing for ML-ProjectKart")

⚙️Things to Note

Make sure you do not copy codes from external sources because that work will not be considered. Plagiarism is strictly not allowed.
You can only work on issues that have been assigned to you.
If you want to contribute the algorithm, it's preferrable that you create a new 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.
Do not update the README.md.

💡Look Through The Kart Of Amazing Projects

S.no	Project Name	Description
1.	Exploratory Data Analysis Of Meteorological Data	It analyzes the meteorological weather data of last 10yrs from 2006 to 2016 at Finland to check an increase of global warming.
2.	Heart Disease Prediction	This project predicts heart disease based on features like age, cholesterol level, blood sugar level etc.
3.	Face Mask Detection Using OpenCV	This a Face Mask Detection project that uses both Haar Cascades and Caffe framework approaches for face detection and a finetuned MobileNetV2 model to detect masks on face taking real time video stream as input.
4.	Emotion Recognition using NLP	An Intelligent Emotion Predictor which uses NLP technique by sending text input to determine whether data is positive, negative or neutral.
5.	Loan Eligibility Prediction	This is a loan eligibility prediction project which will predict the eligibility of a customer for getting a loan from the company using various parameters.
6.	Brain Tumor Detection and Classification	This project detects the presence of brain tumor by processing MRI scans of the patient. If the presence of tumor is detected, it is then classified into ‘Glioma’, ‘Pituitary’ or ‘Meningioma’.
7.	House Prices Prediction	This project predicts the prices of houses located in the cities of US, with the help of essential features.
8.	Icecream Revenue Prediction	This is an icecream revenue prediction which predicts the daily revenue of icecreams depending on the temperature feature.
9.	Uber Fare Prediction	This project helps in predicting the fare to be charged for the Uber travelling person.
10.	Parkinson's Disease Prediction	This project helps in finding the reasons for parkinson's disease and who are predicted to have this disease.
11.	Concrete Strength Prediction	The aim of this project is to predict strength of the concrete from features as fly ash, blast furnamce slag, water, fine aggregate, coarse aggregate, cement, age etc.
12.	Dog Breed Identifiction	Dog Breed Identification helps in predicting the breed of the dogs using an image model
13.	Churn Risk Score Prediction	This project is used to predict the churn score for a website based on the related features
14.	Animate Me	It is a simple OpenCV project that converts input image to a cartoon equivalent
15.	Breast Cancer Prediction	The breast cancer prediction project helps in predicting whether the patient suffering from breast cancer is benign or malignant.
16.	Car Prices Prediction	The main goal is to predict the price of cars with the available independent variables
17.	Iris Flower Classification	The project is to classify the flowers among three 3 different types.
18.	Image Compression Using Clustering	This project helps in compressing the image using K-Means Clustering.
19.	Loan Eligibility Prediction	The main goal of the project is to predict the eligibility of a customer for getting a loan from the company
20.	NASA Asteroids Classification	This project helps in classifying the NASA Asteroids and checks for features responsible for claiming whether the asteroid is hazardous.
21.	Sign Language Prediction	The sign language prediction project helps in identifying the sign language from an image.
22.	Twitter Sentiment Analysis	This project helps in analyzing the sentiment using the text data put on twitter to check it by classifying the statements as positive, negative or neutral.
23.	Uber Fare Prediction	The intention of this project is to predicts the fare to be charged for an uber passenger.

👍OpenSource Program

This project is a part of this open source progam.

Levels & Points

Level	Points
Level 0	5
Level 1	10
Level 2	15
Level 3	30
Level 4	45

✨Hall Of Fame

Thanks goes to these Wonderful People. Contributions of any kind are welcome!🚀

_{Anshul Srivastava}	_Raunak	_{Soumayan Pal}	_{Neeraj Ap}	_{Rutik Bhoyar}	_{Priyanka Hotchandani}	_{Harshita Nayak}
_Sumit	_{Ayushi Shrivastava}	_{Anshal Singh}	_Sidhved	_Jagannath