Learn how to use image classification with Custom Vision, one of the topics covered in the AI-900 certification exam. Find out why you need to train the service before deploying it and generating predictions.
To use the image classification capability with Custom Vision, you just have to deploy the service and then start generating predictions. True or False?
Creating an image classification solution with Custom Vision consists of two main tasks. First, you must use existing images to train the model, and then you must publish the model so that client applications can use it to generate predictions.
The answer to the question is B. False. To use the image classification capability with Custom Vision, you have to do more than just deploy the service and start generating predictions. You also have to train the service with your own custom images and labels, so that it can learn to recognize the categories that you want to classify. Training the service involves uploading images, tagging them with labels, and then training a machine learning model based on the images and labels. After training, you can test the model with new images and evaluate its performance. Only then can you deploy the service and start generating predictions for your own images.
Microsoft Azure AI Fundamentals AI-900 certification exam practice question and answer (Q&A) dump with detail explanation and reference available free, helpful to pass the Microsoft Azure AI Fundamentals AI-900 exam and earn Microsoft Azure AI Fundamentals AI-900 certification.