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articles/cognitive-services/form-recognizer/includes/create-resource.md

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ms.author: pafarley
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When you're granted access to use Form Recognizer, you'll receive a Welcome email with several links and resources. Use the "Azure portal" link in that message to open the Azure portal and create a Form Recognizer resource. In the **Create** pane, provide the following information:
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Go to the Azure Portal and create a new Form Recognizer resource. In the **Create** pane, provide the following information:
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articles/cognitive-services/form-recognizer/overview.md

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Form Recognizer can also extract text and table structure (the row and column numbers associated with the text) using high-definition optical character recognition (OCR).
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## Where do I start?
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## Get started
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**Step 1:** Request access:
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Form Recognizer is available in a limited-access preview. To get access to the preview, fill out and submit the [Form Recognizer access request](https://aka.ms/FormRecognizerRequestAccess) form. The form requests information about you, your company, and the scenario in which you'll use Form Recognizer.
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**Step 2:** Create a Form Recognizer resource in the Azure portal:
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When you're granted access to use Form Recognizer, you'll receive a Welcome email with several links and resources. Use the "Azure portal" link in that message to open the Azure portal and create a Form Recognizer resource.
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**Step 3:** Extract data from your forms:
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Follow a quickstart to get started extracting data from your forms. We recommend that you use the free service when you're learning the technology. Remember that the number of free pages is limited to 500 per month.
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* Custom - train a model to your forms
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* Train without labels
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* Layout - extract text and table structure from forms
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* [Quickstart: Extract layout data using Python](quickstarts/python-layout.md)
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We recommend that you use the free service when you're learning the technology. Remember that the number of free pages is limited to 500 per month.
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**Step 4:** Review the REST APIs:
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### Review the REST APIs
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You'll use the following APIs to train models and extract structured data from forms.
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articles/cognitive-services/form-recognizer/quickstarts/curl-receipts.md

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## Prerequisites
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To complete this quickstart, you must have:
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- Access to the Form Recognizer limited-access preview. To get access to the preview, fill out and submit the [Form Recognizer access request](https://aka.ms/FormRecognizerRequestAccess) form.
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- [cURL](https://curl.haxx.se/windows/) installed.
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- A URL for an image of a receipt. You can use a [sample image](https://github.com/Azure-Samples/cognitive-services-REST-api-samples/blob/master/curl/form-recognizer/contoso-allinone.jpg?raw=true) for this quickstart.
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articles/cognitive-services/form-recognizer/quickstarts/curl-train-extract.md

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## Prerequisites
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To complete this quickstart, you must have:
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- Access to the Form Recognizer limited-access preview. To get access to the preview, fill out and submit the [Form Recognizer access request](https://aka.ms/FormRecognizerRequestAccess) form.
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- [cURL](https://curl.haxx.se/windows/) installed.
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- A set of at least six forms of the same type. You will use five of these to train the model, and then you'll test it with the sixth form. Your forms can be of different file types but must be the same type of document. You can use a [sample data set](https://go.microsoft.com/fwlink/?linkid=2090451) for this quickstart. Upload the training files to the root of a blob storage container in an Azure Storage account. You can put the testing files in a separate folder.
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articles/cognitive-services/form-recognizer/quickstarts/dotnet-sdk.md

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## Prerequisites
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* Azure subscription - [Create one for free](https://azure.microsoft.com/free/).
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* Access to the Form Recognizer limited-access preview. To get access to the preview, fill out and submit the [Form Recognizer access request](https://aka.ms/FormRecognizerRequestAccess) form.
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* An Azure Storage blob that contains a set of training data. See [Build a training data set for a custom model](../build-training-data-set.md) for tips and options for putting together your training data. For this quickstart, you can use the files under the **Train** folder of the [sample data set](https://go.microsoft.com/fwlink/?linkid=2090451).
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* The current version of [.NET Core](https://dotnet.microsoft.com/download/dotnet-core).
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articles/cognitive-services/form-recognizer/quickstarts/label-tool.md

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## Prerequisites
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To complete this quickstart, you must have:
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- Access to the Form Recognizer limited-access preview. To get access to the preview, fill out and submit the [Form Recognizer access request form](https://aka.ms/FormRecognizerRequestAccess). You'll receive an email with a link to create a Form Recognizer resource.
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- Access to the Form Recognizer sample labeling tool. To get access, fill out and submit the [Form Recognizer label tool request form](https://aka.ms/LabelToolRequestAccess). You'll receive an email with instructions on how to obtain your credentials and access the private container registry.
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- A set of at least six forms of the same type. You'll use this data to train the model and test a form. You can use a [sample data set](https://go.microsoft.com/fwlink/?linkid=2090451) for this quickstart. Upload the training files to the root of a blob storage container in an Azure Storage account.
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articles/cognitive-services/form-recognizer/quickstarts/python-labeled-data.md

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## Prerequisites
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To complete this quickstart, you must have:
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- Access to the Form Recognizer limited-access preview. To get access to the preview, fill out and submit the [Form Recognizer access request](https://aka.ms/FormRecognizerRequestAccess) form.
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- [Python](https://www.python.org/downloads/) installed (if you want to run the sample locally).
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- A set of at least six forms of the same type. You will use this data to train the model and test a form. You can use a [sample data set](https://go.microsoft.com/fwlink/?linkid=2090451) for this quickstart. Upload the training files to the root of a blob storage container in an Azure Storage account.
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articles/cognitive-services/form-recognizer/quickstarts/python-layout.md

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## Prerequisites
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To complete this quickstart, you must have:
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- Access to the Form Recognizer limited-access preview. To get access to the preview, fill out and submit the [Form Recognizer access request](https://aka.ms/FormRecognizerRequestAccess) form.
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- [Python](https://www.python.org/downloads/) installed (if you want to run the sample locally).
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- A form document. You can download an image from the [sample data set](https://go.microsoft.com/fwlink/?linkid=2090451) for this quickstart.
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articles/cognitive-services/form-recognizer/quickstarts/python-receipts.md

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## Prerequisites
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To complete this quickstart, you must have:
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- Access to the Form Recognizer limited-access preview. To get access to the preview, fill out and submit the [Form Recognizer access request](https://aka.ms/FormRecognizerRequestAccess) form.
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- [Python](https://www.python.org/downloads/) installed (if you want to run the sample locally).
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- A URL for an image of a receipt. You can use a [sample image](https://github.com/Azure-Samples/cognitive-services-REST-api-samples/blob/master/curl/form-recognizer/contoso-allinone.jpg?raw=true) for this quickstart.
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articles/cognitive-services/form-recognizer/quickstarts/python-train-extract.md

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## Prerequisites
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To complete this quickstart, you must have:
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- Access to the Form Recognizer limited-access preview. To get access to the preview, fill out and submit the [Form Recognizer access request](https://aka.ms/FormRecognizerRequestAccess) form.
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- [Python](https://www.python.org/downloads/) installed (if you want to run the sample locally).
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- A set of at least five forms of the same type. You will use this data to train the model. Your forms can be of different file types but must be the same type of document. You can use a [sample data set](https://go.microsoft.com/fwlink/?linkid=2090451) for this quickstart. Upload the training files to the root of a blob storage container in an Azure Storage account.
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