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Udacity Self-Driving Car Engineer Term 1: Traffic Sign Classifier project

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Project: Build a Traffic Sign Recognition Program

Udacity - Self-Driving Car NanoDegree

Overview

The goal of this project is to use deep neural networks and convolutional neural networks to classify traffic signs. The data used is the German Traffic Sign Dataset, and the model was also verified on images of German traffic signs found on the web. Check out my writeup to learn more about my process and see how it works.

Dependencies

This lab requires:

The lab environment can be created with CarND Term1 Starter Kit. Click here for the details.

Dataset and Repository

  1. Download the data set. The classroom has a link to the data set in the "Project Instructions" content. This is a pickled dataset in which we've already resized the images to 32x32. It contains a training, validation and test set.
  2. Clone the project, which contains the Ipython notebook and the writeup template.
git clone https://github.com/udacity/CarND-Traffic-Sign-Classifier-Project
cd CarND-Traffic-Sign-Classifier-Project
jupyter notebook Traffic_Sign_Classifier.ipynb

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Udacity Self-Driving Car Engineer Term 1: Traffic Sign Classifier project

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