Book Image

Practical Guide to Azure Cognitive Services

By : Chris Seferlis, Christopher Nellis, Andy Roberts
Book Image

Practical Guide to Azure Cognitive Services

By: Chris Seferlis, Christopher Nellis, Andy Roberts

Overview of this book

Azure Cognitive Services and OpenAI are a set of pre-built artificial intelligence (AI) solution APIs that can be leveraged from existing applications, allowing customers to take advantage of Microsoft’s award-winning Vision, Speech, Text, Decision, and GPT-4 AI capabilities. With Practical Guide to Azure Cognitive Services, you’ll work through industry-specific examples of implementations to get a head-start in your production journey. You’ll begin with an overview of the categorization of Azure Cognitive Services and the benefits of embracing AI solutions for practical business applications. After that, you’ll explore the benefits of using Azure Cognitive Services to optimize efficiency and improve predictive capabilities. Then, you’ll learn how to leverage Vision capabilities for quality control, Form Recognizer to streamline supply chain nuances, language understanding to improve customer service, and Cognitive Search for next-generation knowledge-mining solutions. By the end of this book, you’ll be able to implement various Cognitive Services solutions that will help you enhance efficiency, reduce costs, and improve the customer experience at your organization. You’ll also be well equipped to automate mundane tasks by reaping the full potential of OpenAI.
Table of Contents (22 chapters)
1
Part 1: Ocean Smart – an AI Success Story
5
Part 2: Deploying Next-Generation Knowledge Mining Solutions with Azure Cognitive Search
10
Part 3: Other Cognitive Services That Will Help Your Company Optimize Operations

Using Smart Labeler for faster image labeling

So, now we have reached a point where we have built a model using our images of what a “good” or “bad” frozen lobster tail should look like. As we need to add more images to the model for training and accuracy improvement, we can use the Smart Labeler feature to quicken the process of tagging new images.

Getting started with the process is fairly straightforward now that we already have our model built and a sample set of images loaded. You will simply upload new images within the project using the previous steps, but don’t tag them as you upload them. The images will upload and be labeled as Untagged, with the option to Get suggested tags, as shown in the following figure:

Figure 10.11 – Smart Labeler dialog box displaying Tagged and Untagged image options

Figure 10.11 – Smart Labeler dialog box displaying Tagged and Untagged image options

When we select the Get suggested tags option, we then get the option to choose how many images we want to tag...