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Full Stack Premier League with PostgresSQL database, data scraping and React

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PremierZone

PremierZone is a comprehensive project designed to scrape match statistics for over 700 players, manipulate and present the data dynamically, and predict match outcomes using machine learning. The project is divided into four main components: Backend, Frontend, Data Scraping, and Machine Learning.

Screenshot 2024-06-22 at 11 29 13 PM

You can find the project here!
Note: The backend is currently not being hosted, this will be fixed in one to two business weeks...

Features

  • Data Scraping: Engineered a comprehensive data scraping of match statistics for 700+ players using Python and pandas.
  • Backend: Dynamic manipulation and presentation of the scraped data through a Spring Boot application.
  • Database: Real-time data manipulation within a Postgres database using SQL queries.
  • Frontend: Seamless integration with a user-friendly ReactJS interface.
  • Machine Learning: Created a model to predict match outcomes by integrating data scraping with pandas and machine learning with scikit-learn.

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Full Stack Premier League with PostgresSQL database, data scraping and React

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