The Air Pressure System (APS) is a critical component of a heavy-duty vehicle that
uses compressed air to force a piston to provide pressure to the brake pads, slowing
the vehicle down. The benefits of using an APS instead of a hydraulic system are the
easy availability and long-term sustainability of natural air.
This is a Binary Classification problem, in which the affirmative class indicates that the
failure was caused by a certain component of the APS, while the negative class
indicates that the failure was caused by something else.
Check out the project demo at https://youtu.be/8IcTGZ6nDA0
Check out the deployed app at https://shivamshinde123-scania-truck-failures-predicti-srcwebapp-rkeg3t.streamlit.app/
Get the data from https://archive-beta.ics.uci.edu/dataset/421/aps+failure+at+scania+trucks
APS Failure at Scania Trucks. (2017). UCI Machine Learning Repository.
Clone the project
git clone https://github.com/shivamshinde123/Scania-Truck-Failures-Prediction.git
Go to the project directory
cd project-name
Create a conda environment
conda create -n environment_name python=3.10
Activate the created conda environment
conda activate environment_name
Install dependencies
pip install -r requirements.txt
Load the data --> Preprocess the data --> Train the model --> Evaluate the model --> Plot the evaluations --> Testing code
dvc repro
Make predictions using trained model
streamlit run src/webapp.py
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