Overview
Deep learning is a subfield of machine learning. It uses methods based on learning data representations and structures such as neural networks.
Keras is a high-level neural networks API for fast development and experimentation. It runs on top of TensorFlow, CNTK, or Theano.
This instructor-led, live training (online or onsite) is aimed at developers who wish to build a self-driving car (autonomous vehicle) using deep learning techniques.
By the end of this training, participants will be able to:
- Use Keras to build and train a convolutional neural network.
- Use computer vision techniques to identify lanes in an autonomos driving project.
- Train a deep learning model to differentiate traffic signs.
- Simulate a fully autonomous car.
Format of the Course
- Interactive lecture and discussion.
- Lots of exercises and practice.
- Hands-on implementation in a live-lab environment.
Course Customization Options
- To request a customized training for this course, please contact us to arrange.
Requirements
- Python programming experience.
Audience
- Developers
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