license:unknown region:us
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license: unknown
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The project revolves around creating a deep neural network that can classify traffic signs present in the image into different categories. 
With this model, we are able to read and understand traffic signs with 98% accuracy. 
Our approach to building this traffic sign classification model is discussed in four steps: 
- Exploring the dataset and some visualizations
- Splitting the dataset into training and testing data
- Building the CNN model
- Training and validating the model
- Testing the model with the testing dataset
