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This is a template for creating a Machine Learning application with its front-end developed using React which interacts with a Flask service as the back-end and makes predictions.
This project scrapes Wikipedia for its articles using BeautifulSoup to create a dataset and then draws analysis on the collected data.
This project explores the usage of Flask and Flask-RESTPlus in developing a Python service to host any application as well as exploring APIs (and Swagger UI).
This repository explores various Numpy commands which are quite useful for working with datasets and handling array operations.
The project involves training a machine learning model (K Neighbors Classifier) to predict whether someone is suffering from a heart disease with 87% accuracy.
This project explores colors in various images and then enables the user to query the images based on a given color.
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