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Traffic Accident Prediction Model using Deep Learning #930
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Our team will soon review your PR. Thanks @alo7lika :) |
@abhisheks008 the task has been completed. |
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Hi @alo7lika please go through the README.md and follow the project structure.
Sharing the project structure,
Project Folder
|- Dataset
|- dataset.csv (dataset used for the particula project)
|- README.md (brief about the dataset)
|- Images
|- img1.png
|- img2.png
|- img3.png
|- Model
|- project_folder.ipynb
|- README.md
|- requirements.txt
done @abhisheks008 |
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I couldn't find the required project structure for this project.
This has to be like this,
Project Folder
|- Dataset
|- dataset.csv (dataset used for the particula project)
|- README.md (brief about the dataset)
|- Images
|- img1.png
|- img2.png
|- img3.png
|- Model
|- project_folder.ipynb
|- README.md
|- requirements.txt
…ng /Model/Model/READ,E.md to Traffic Accident Prediction Model using Deep Learning /requirement.txt
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What about the Images and Dataset folder. You need to do them as well.
@alo7lika
My project doesn't contain dataset since I have used synthetic dataset and also no images as well |
You haven't perform any EDA? If you don't have a dataset, then just create a folder named as Dataset. Inside that, put a README.md file and mention a brief about the dataset you have used there. |
done @abhisheks008 |
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Looks good to me. Approved!
@alo7lika
Pull Request for DL-Simplified 💡
#905
Issue Title: Traffic Accident Prediction Model Using Deep Learning
Info about the related issue (Aim of the project): The goal of this project is to develop a machine learning model that predicts the likelihood of traffic accidents based on historical data, weather conditions, traffic volume, and road characteristics. The model aims to provide insights that can help in making informed decisions to enhance road safety.
Name: Alolika Bhowmik
GitHub ID: alo7lika
Email ID: [email protected]
Identify yourself:
Gssoc Ext 24 Contributor
Closes: #905
Describe the add-ons or changes you've made 📃
I have implemented a deep learning model using LSTM (Long Short-Term Memory) networks to analyze and predict traffic accident probabilities. The following changes have been made:
Type of change ☑️
What sort of change have you made:
How Has This Been Tested? ⚙️
The model has been tested using a separate validation dataset. I have verified the accuracy of the predictions against known accident data. Additionally, the code has been run in a local environment to ensure that all components work together seamlessly without errors.
Checklist: ☑️