This course will teach you how to use and work with Azure Cognitive Services: Forms Recognizer, which extracts text and data from scanned documents, going beyond traditional OCR. It is also able to learn from new document models.
Azure Cognitive Services: Forms Recognizer can help you better maintain compliance with document archival rules by flagging data that may require manual input. In this course, Microsoft Azure Cognitive Services: Forms Recognizer, you will learn to use OCR technology built into Azure to extract text and key-value pairs of data from PDF documents and images.
First, you will explore how to detect printed text within an image or PDF document.
Next, you will discover how to detect key-value pairs in images or PDF documents automatically so that they can retain the inherent context of the document without any manual intervention.
Then, you will learn how to use Forms Recognizer’s machine learning capabilities to add new document layouts and types of documents, known as models.
Finally, you will understand how to preserve the composition of data stored in tables during extraction.
When finished with this course, you will have the skills and knowledge of how to use the Forms Recognizer service to create smart search indexes, build automated approval workflows, as well as being able to export data contained within those documents to other systems.
Eduardo is a technology enthusiast, software architect and customer success advocate. He's designed enterprise .NET solutions that extract, validate and automate critical business processes such as Accounts Payable and Mailroom solutions. He's a well-known specialist in the Enterprise Content Management market segment, specifically focusing on data capture & extraction and document process automation.
Course Overview Hi everyone. Welcome to my course, Microsoft Azure Cognitive Services: Form Recognizer. I'm a software developer, a data capture and business automation specialist. Form Recognizer is an Azure Cognitive Service that automatically uses machine learning technology to identify and extract key‑value pairs and table data from Form documents. Form Recognizer uses unsupervised learning, which allows the system's model to understand the layout and field data without manual data labeling or intensive coding. With Form Recognizer it is also possible to perform data labeling when using custom forms to create better performing models and achieve better recognition results. By using Form Recognizer you'll be able to analyze forms and documents and make data‑driven decisions by extracting data from tables and forms. You'll also be able to extract texts, key‑value pairs, and tables from forms and receipts. Some of the major topics we will cover include layout fundamentals, bounding boxes, prebuilt model with Python, extracting table data, training with labels, and using custom models. And finally, watching these technologies and principles getting applied by creating our own Python scripts with some very cool demos. By the end of this course you'll know the fundamentals of working with Form Recognizer and be able to write code that uses it. Before beginning the course you should have some knowledge of Python, as well as being able to find your way around with the latest version of Visual Studio Code. I hope you will join me on this journey to learn the ins and outs of Microsoft Azure Cognitive Services Form Recognizer at Pluralsight.