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Data ScienceAdvanced

Advanced Deep Learning Techniques for Computer Vision

Visual inspection and medical imaging are two applications that aim to find anything unusual in images. In this course, you’ll train and calibrate specialized...

By Mehdi Alemi on Coursera

About This Course

Visual inspection and medical imaging are two applications that aim to find anything unusual in images. In this course, you’ll train and calibrate specialized models known as anomaly detectors to identify defects. You’ll also use advanced techniques to overcome common data challenges with deep learning. AI-assisted labeling is a technique to auto-label images, saving time and money when you have tens of thousands of images. If you have too few images, you’ll generate synthetic training images using data augmentation for situations where acquiring more data is expensive or impossible. 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.

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Frequently Asked Questions

How much does Advanced Deep Learning Techniques for Computer Vision cost?

Visit the Advanced Deep Learning Techniques for Computer Vision course page for current pricing and available discounts.

Who teaches Advanced Deep Learning Techniques for Computer Vision?

Advanced Deep Learning Techniques for Computer Vision is taught by Mehdi Alemi, MathWorks.

What skill level is Advanced Deep Learning Techniques for Computer Vision for?

This course is designed for advanced learners.

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Students0
DurationSelf-paced
LevelAdvanced
Languageen
PlatformCoursera
InstructorMehdi Alemi