Learning Objectives - Describe Features of Computer Vision Workloads on Azure (15-20%)

The video tutorial covers the learning objectives of a module on computer vision workloads. It begins with an overview of various computer vision features such as image classification, object detection, and facial recognition. The tutorial then explores how to implement these features using Azure's pre-trained models and services, including the Computer Vision and Face services. For applications with specific needs, the Custom Vision service is introduced, allowing users to train their own models. The module includes numerous demos and examples to illustrate these concepts.

Which of the following is NOT a feature of computer vision workload discussed in the module?

• Natural language processing

• Optical character recognition

• Object detection

• Image classification

Which of the following is a face-related feature discussed in the module?

• Facial detection

• Voice recognition

• Gesture control

• Emotion analysis

What is the primary benefit of using pre-trained models in Azure for computer vision tasks?

• They are faster to deploy

• They are more accurate than custom models

• They require no additional training

• They are cheaper to use

If a pre-trained model does not meet specific application needs, what service does Azure offer?

• Custom Vision Service

• Azure Cognitive Search

• Azure Machine Learning

• Azure Data Factory

What is emphasized in the final section of the module?

• Future trends in computer vision

• Historical background

• Practical applications and demos

• Theoretical concepts