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articles/ai-services/language-service/sentiment-opinion-mining/custom/quickstart.md

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ms.service: azure-ai-language
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ms.topic: quickstart
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ms.date: 12/19/2023
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ms.date: 01/25/2024
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ms.author: aahi
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ms.custom: language-service-sentiment-opinion-mining
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zone_pivot_groups: usage-custom-language-features
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---
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# Quickstart: Custom sentiment analysis
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# Quickstart: Custom sentiment analysis (preview)
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Use this article to get started with creating a Custom sentiment analysis project where you can train custom models for detecting the sentiment of text. A model is artificial intelligence software that's trained to do a certain task. For this system, the models classify text, and are trained by learning from tagged data.
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articles/ai-services/language-service/sentiment-opinion-mining/overview.md

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ms.topic: overview
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ms.custom: language-service-sentiment-opinion-mining, ignite-fall-2021
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[!INCLUDE [Developer reference](../includes/reference-samples-text-analytics.md)]
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#### [Custom model](#tab/custom)
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#### [Custom model (preview)](#tab/custom)
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Custom sentiment analysis enables users to build custom AI models to classify text into sentiments pre-defined by the user. By creating a Custom sentiment analysis project, developers can iteratively label data, train, evaluate, and improve model performance before making it available for consumption. The quality of the labeled data greatly impacts model performance. To simplify building and customizing your model, the service offers a custom web portal that can be accessed through the [Language studio](https://aka.ms/languageStudio). You can easily get started with the service by following the steps in this [quickstart](quickstart.md).
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articles/ai-services/language-service/sentiment-opinion-mining/quickstart.md

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# ms.devlang: csharp, java, javascript, python

articles/ai-services/language-service/toc.yml

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