Traffic Sign Classification Using Deep Learning in Python/Keras

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In this Guided Project, you will:
2 hours
Intermediate
No download needed
Split-screen video
English
Desktop only

In this 1-hour long project-based course, you will be able to: - Understand the theory and intuition behind Convolutional Neural Networks (CNNs). - Import Key libraries, dataset and visualize images. - Perform image normalization and convert from color-scaled to gray-scaled images. - Build a Convolutional Neural Network using Keras with Tensorflow 2.0 as a backend. - Compile and fit Deep Learning model to training data. - Assess the performance of trained CNN and ensure its generalization using various KPIs. - Improve network performance using regularization techniques such as dropout.

Skills you will develop

  • Deep Learning

  • Artificial Intelligence (AI)

  • Machine Learning

  • Python Programming

  • Computer Vision

Learn step-by-step

In a video that plays in a split-screen with your work area, your instructor will walk you through these steps:

How Guided Projects work

Your workspace is a cloud desktop right in your browser, no download required

In a split-screen video, your instructor guides you step-by-step

Instructor

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