Learn how to train a classification model with Azure Custom Vision, a cloud-based service that allows you to create custom image classification models without coding.
Table of Contents
Question
To train a classification model, you must upload images to your training resource and label them with the appropriate class labels. True or False?
A. True
B. False
Answer
A. True
Explanation
To train a classification model, you must upload images to your training resource and label them with the appropriate class labels.
The correct answer is A. True. To train a classification model, you must upload images to your training resource and label them with the appropriate class labels. This is because a classification model is a type of supervised learning algorithm that assigns a category or a class to an input image based on its features. For example, a classification model can identify whether an image contains a dog or a cat. To train such a model, you need to provide it with a set of labeled images, where each image has a class label that indicates what it contains. The model then learns to recognize the patterns and features that distinguish different classes from each other. The more images and labels you provide, the more accurate the model will be.
To upload and label images for a classification model, you can use the Azure Custom Vision service, which is a part of the Azure Cognitive Services. Azure Custom Vision is a cloud-based service that allows you to easily create and deploy custom image classification models without any coding or machine learning expertise. You can use the Azure Custom Vision portal or the Custom Vision SDK to upload your images and assign them to different classes or tags. You can also use the portal or the SDK to train, test, and publish your model as an endpoint that can be accessed by other applications.
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