The Complete Self-Driving Car Course - Applied Deep Learning
Use deep learning, Computer Vision, and machine learning techniques to build an autonomous car with Python
Created by Rayan Slim, Jad Slim, Amer Abdulkader, Sarmad Tanveer
Explore how deep learning and computer vision come together to power autonomous vehicles. You'll use Python and practical machine learning techniques to build your own self-driving car simulation. Gain hands-on experience with neural networks and see your code in action as you tackle real-world challenges.
Packt | Apr 2019 | 1080 min
What You Will Learn
You'll start by working with computer vision tools to analyze road images, then move on to building and training neural networks using Python and Keras. Each step involves hands-on projects that reinforce concepts, so you'll see immediate results as you develop and refine your self-driving car simulation.
Key Features
- Apply computer vision to detect lanes and interpret road signs for autonomous driving
- Build and train neural networks using Keras to solve complex automotive tasks
- Simulate a fully functional self-driving car and understand deep learning workflows
Target Audience
Ideal for developers or tech enthusiasts with some programming experience who want to break into artificial intelligence and autonomous systems. If you're aiming to build practical deep learning skills and apply them to real-world automotive challenges, you'll find this course a great fit.
