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Course Outline
Introduction
Setting up the Development Environment
Creating a Project
Configuring the Simulator
Preparing the Data Sets
Overview of Python Deep Learning Libraries
Applying Computer Vision Techniques to Track Lanes
Training Perceptron-Based Neural Networks to Detect Other Vehicles
Implementing Convolutional Neural Networks to Predict Steering Angle and Speed
Training a Deep Learning Model to Classify Traffic Signs
Using Polynomial Regression to Improve Predictive Accuracy
Testing the Self Driving Car
Troubleshooting
Summary and Conclusion
Requirements
- Python programming experience.
Audience
- Developers
21 Hours
Testimonials (2)
Trainer was very knowlegable and very open to feedback on what pace to go through the content and the topics we covered. I gained alot from the training and feel like I now have a good grasp of image manipulation and some techniques for building a good training set for an image classification problem.
Anthea King - WesCEF
Course - Computer Vision with Python
I genuinely enjoyed the hands-on approach.
