Fundamentals of Deep Learning for Computer Vision

In this hands-on course, you will learn the basics of deep learning by training and deploying neural networks. You will:

- Implement common deep learning workflows such as Image Classification and Object Detection.
- Experiment with data, training parameters, network structure, and other strategies to increase performance and capability.
- Deploy your networks to start solving real-world problems

On completion of this course, you will be able to start solving your own problems with deep learning.

What You'll Learn

• Identify the ingredients required to start a Deep Learning project.
• Train a deep neural network to correctly classify images it has never seen before.
• Deploy deep neural networks into applications.
• Identify techniques for improving the performance of deep learning applications.
• Assess the types of problems that are candidates for deep learning.
• Modify neural networks to change their behavior.

• Unlocking New Capabilities 
  1. Big Bang in Deep Learning: Introduction 
  2. Deep Neural Networks: 45 minutes 
  3. The GPU:20 minutes 
  4. Big Data: 45 minutes 
• Creating Applications that Use Deep Learning 
  1. A Deep Learning Project: Introduction 
  2. Simple Deployment: 45 minutes 
• Measuring and Improving Performance 
  1. Categories of Performance 
  2. Deploying Pretrained Networks 
  3. Beyond Image Classification 
  4. End Of Course 
• Assessment 
  1. Train and deploy a deep neural network. 
• Next Steps 
  1. Next Steps