image for course Deep Learning with MATLAB

Deep Learning with MATLAB

Implement common deep learning workflows in MATLAB® using real-world image and sequence data. Dive into some of the ideas behind deep learning algorithms and standard network architectures.

Course modules

Classifying Images with Convolutional Networks

Get an overview of the course. Perform image classification using pretrained networks. Use transfer learning to train customized classification networks.

Lessons:
  • Course Overview
  • Deep Learning Basics

Understanding Convolutional Neural Networks

Understand how information is passed between network layers and how different types of layers work.

Lessons:
  • Understanding Neural Networks
  • Convolutional Layers
  • Viewing Filters
  • Viewing the Activations of Different Layers
  • Review - Understanding Convolutional Neural Networks

Creating and Training Networks

Train networks from scratch. Understand how training algorithms work. Set training options to monitor and control training.

Lessons:
  • Training from Scratch
  • Creating Network Architectures
  • Understanding Network Training
  • Monitoring Training Progress
  • Validation
  • Review - Creating and Training Networks

Improving Performance

Choose and implement modifications to training algorithm options and training data to improve network performance.

Lessons:
  • Troubleshooting Methods
  • Visualizing Network Predictions
  • Augmented Datastores
  • Training Options
  • Experiment Manager
  • Review - Improving Performance

Image Classification Project

Bring together image classification concepts that you have learned with a project.

Lessons:
  • Project - Classify Fashion Images

Performing Regression

Create convolutional networks that can predict continuous numeric responses.

Lessons:
  • What is Regression
  • Transfer Learning for Regression
  • Evaluating a Regression Network
  • Review - Performing Regression

Using Deep Learning for Computer Vision

Train networks to locate and label specific objects within images.

Lessons:
  • Computer Vision Applications
  • Ground Truth
  • YOLO Object Detectors
  • Evaluating Object Detectors
  • Review - Deep Learning for Computer Vision

Classifying Sequence Data with Recurrent Networks

Build and train networks to perform classification on ordered sequences of data, such as time series or sensor data.

Lessons:
  • Course Example - Classify Flooding Level
  • Managing Collections of Signal Data
  • Long Short-Term Memory Networks
  • Sequence Classification
  • Improving LSTM Performance
  • Review - Classifying Sequence Data with Recurrent Networks

Classifying Sequences of Output

Use recurrent networks to create sequences of predictions.

Lessons:
  • Course Example - Classify Regions of Flooding Levels
  • Labeling Regions of Interest
  • Sequence-to-Sequence Classification
  • Review - Classifying Sequences of Output

Sequence Classification Project

Bring together signal classification concepts that you have learned with a project.

Lessons:
  • Project - Robot Navigation

Conclusion

Learn next steps and give feedback on the course.

Lessons:
  • Summary
  • Additional Resources
  • Survey

Format:Self-paced

Language:English

Language

  • Hands-on exercises with automated feedback
  • Access to MATLAB through your web browser
  • Shareable progress report and course certificate

Machine Learning with MATLAB

Explore data and build predictive models.

Image Processing with MATLAB

Learn practical image processing workflows in MATLAB.

Reinforcement Learning Onramp

Master the basics of creating intelligent controllers that learn from experience.

Deep Learning Onramp

Get started quickly using deep learning methods to perform image recognition.