Ementorhub

Advanced Deep Learning Techniques for Computer Vision

This course is part of multiple programs. Learn more

Instructors: Mehdi Alemi +4 more

What you'll learn

Train and calibrate specialized models known as anomaly detectors

Generate synthetic training images for situations where acquiring more data is expensive or impossible

Use AI-assisted auto-labeling to save time and money

Import models from 3rd party tools like PyTorch and export your model outside of MATLAB

Skills you'll gain

Computer Vision

Application Deployment

Matlab

Image Analysis

Anomaly Detection

Deep Learning

Applied Machine Learning

Medical Imaging

Data Synthesis

PyTorch (Machine Learning Library)

There are 4 modules in this course

By the end of this course, you will be able to: • Train anomaly detection models • Generate synthetic training images using data augmentation • Use AI-assisted annotation to label images and video files • Import models from 3rd party tools like PyTorch • Describe approaches to using your model outside of MATLAB For the duration of the course, you will have free access to MATLAB, software used by top employers worldwide. The courses draw on the applications using MATLAB, so you spend less time coding and more time applying deep learning concepts.

Data Augmentation

Model-Assisted Labeling

Creating Your Own Models

Explore more from Machine Learning

Deep Learning for Computer Vision

Deep Learning for Object Detection

Introduction to Deep Learning for Computer Vision

Deep Learning Applications for Computer Vision