[Code Addition Request]: Traffic Accident Prediction Model using Deep Learning

[alo7lika]

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Project Description

Aim: To develop a deep learning model that predicts the likelihood of traffic accidents based on historical data and various contributing factors, ultimately enhancing road safety.

Dataset: Historical traffic accident data, including features like weather conditions, traffic volume, time of day, and geographical location.

Approach: Implement a Recurrent Neural Network (RNN) model, specifically using Long Short-Term Memory (LSTM) networks. The model will focus on time-based patterns in the traffic accident data to predict future events based on historical data. The project will include exploratory data analysis (EDA) to understand the dataset's characteristics and distributions, ensuring that EDA includes visualizations of the relationships between features and the target variable.

Full Name

Alolika bhowmik

Participant Role

Contributor GSSOC EXT 24

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[alo7lika]

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