Group 2 - Final Project for the UTK Machine Learning Course (COSC-522)
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Updated
Dec 12, 2021 - Jupyter Notebook
Group 2 - Final Project for the UTK Machine Learning Course (COSC-522)
ML-powered dashboard for US traffic accident severity prediction using AutoML, PyCaret, and Streamlit.
Exploratory Data Analysis on road accidents happened in 5 years in US that can help in prevention of accidents.
Exploratory Data Analysis on the US Accidents Dataset using Python, Pandas, Seaborn, and Folium to analyze accident trends, patterns, and geospatial distributions.
Trabajo de promoción | Bases de Datos 2 (2022) | UNLP Informática (4º año) | Spring - PostgreSQL - MongoDB - Docker Compose - US Traffic Accidents Dataset
This project is a comprehensive machine learning project developed to analyze and predict traffic accidents in the United States. The project works with over 7.7 million accident data collected between 2016-2023 and provides an interactive web application for real-time predictions.
This project is a comprehensive machine learning project developed to analyze and predict traffic accidents in the United States. The project works with over 7.7 million accident data collected between 2016-2023 and provides an interactive web application for real-time predictions.
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