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In this workshop, you help Contoso Ltd. build a proof of concept that shows how they can develop a solution that amplifies their agents' claims processing capabilities.
They would like to automatically classify each claim detail a customer types in as either home or auto, based on the text. This classification should be displayed in the claim summary, so an agent can quickly assess whether they are dealing with purely a home claim, an auto claim, or a claim with a mixture of the two.
They would also like to experiment with applying sentiment analysis to the claim text. Contoso Ltd. knows most customers are either factual in their description (a neutral sentiment) or slightly unhappy (a more negative sentiment). They believe that negative sentiment can indicate that the claim text involves a more severe situation, which might warrant an agent's expedited review.
Next, they would like to summarize long claim text automatically. This summarization would enable the agent to get the gist before reading the full claim and quickly remind themselves of the context when revisiting it.
Finally, they would like to automatically extract information from the photos submitted with the claims to increase their searchability.
January 2021
In this workshop, you learn to combine both pre-built artificial intelligence (AI) in the form of various Cognitive Services with custom AI in the form of services built and deployed with Azure Machine Learning service. You will learn to create intelligent solutions atop unstructured text data by designing and implementing a text analytics pipeline. You will also learn how to build a binary classifier using a recurrent neural network that can be used to classify the textual data. You will also learn how to deploy multiple kinds of predictive services using Azure Machine Learning and learn to integrate with the Computer Vision API and the Text Analytics API from Cognitive Services.
At the end of this workshop, you will be better able to present solutions leveraging Azure Machine Learning service, Azure Machine Learning compute instance, and Cognitive Services.
In this whiteboard design session, you work with a group to design a solution that combines both pre-built artificial intelligence (AI) in the form of various Cognitive Services with custom AI in the form of services built and deployed with Azure Machine Learning services. You will learn to create intelligent solutions atop unstructured text data by designing and implementing a text analytics pipeline. You will discover how to build a binary classifier using a recurrent neural network that can be used to classify the textual data. You will also learn how to deploy multiple kinds of predictive services using Azure Machine Learning and learn to integrate with the Computer Vision API and the Text Analytics API from Cognitive Services.
At the end of this whiteboard design session, you will be better able to design solutions leveraging Azure Machine Learning services and Cognitive Services.
In this hands-on lab, you implement a solution that combines both pre-built artificial intelligence (AI) in the form of various Cognitive Services with custom AI in the form of services built and deployed with Azure Machine Learning service. In the lab, you work with unstructured text and image data and learning how to develop analytics pipelines for various problems such as text summarization, text classification, image detection, optical character recognition (OCR), and sentiment analysis. You learn how to build and train a deep neural net for text classification. You also learn how to deploy multiple kinds of predictive services using Azure Machine Learning and learn to integrate with the Computer Vision API and the Text Analytics API from Cognitive Services.
At the end of this hands-on lab, you will be better able to present solutions leveraging Azure Machine Learning service, Azure Machine Learning compute instance, and Cognitive Services.
- Azure Machine Learning service
- Cognitive Services
- Computer Vision API
- Text Analytics API
- TensorFlow
- Keras
- ONNX
Machine Learning
We welcome feedback and comments from Microsoft SMEs & learning partners who deliver MCWs.
Having trouble?
- First, verify you have followed all written lab instructions (including the Before the Hands-on lab document).
- Next, submit an issue with a detailed description of the problem.
- Do not submit pull requests. Our content authors will make all changes and submit pull requests for approval.
If you are planning to present a workshop, review and test the materials early! We recommend at least two weeks prior.
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