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
Testimonials (2)
The hands-on approach
Kevin De Cuyper
Course - Computer Vision with OpenCV
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.