我们之前介绍了 Document AI 专用处理器,以及它们如何通过提供一致的架构和标准化数据来提供有关特定文档类型的智能数据分析,从而减少您需要执行的前/后处理工作量。借助 Document AI Workbench,您无需具备机器学习专业知识,即可增量训练预训练处理器,以及从头开始创建自定义处理器。
[[["易于理解","easyToUnderstand","thumb-up"],["解决了我的问题","solvedMyProblem","thumb-up"],["其他","otherUp","thumb-up"]],[["很难理解","hardToUnderstand","thumb-down"],["信息或示例代码不正确","incorrectInformationOrSampleCode","thumb-down"],["没有我需要的信息/示例","missingTheInformationSamplesINeed","thumb-down"],["翻译问题","translationIssue","thumb-down"],["其他","otherDown","thumb-down"]],["最后更新时间 (UTC):2025-09-02。"],[[["\u003cp\u003eThis content introduces Document AI, a tool for extracting insights from unstructured data in documents like PDFs and emails, to automate processes and gather analytics.\u003c/p\u003e\n"],["\u003cp\u003eThe videos and labs demonstrate how to use Document AI via the Google Cloud console or API, including creating and managing Document AI processors.\u003c/p\u003e\n"],["\u003cp\u003eGeneral processors, which are pre-trained models for any document type, are covered to learn how to get structured information from documents.\u003c/p\u003e\n"],["\u003cp\u003eSpecialized processors, designed for documents such as invoices, tax documents, and ID cards, are discussed to get the best intelligent insights from specific document types.\u003c/p\u003e\n"],["\u003cp\u003eDocument AI Workbench is introduced, highlighting its capabilities for up-training pre-trained processors and creating custom processors without requiring machine learning expertise.\u003c/p\u003e\n"]]],[],null,["# Introduction videos & labs\n\nIntroduction videos \\& labs\n===========================\n\nThe videos on this page cover the fundamental concepts of Document AI.\nEach video has companion labs which provide step-by-step guides to get\nexperience using the features presented in the video.\n\nWhat is Document AI?\n--------------------\n\nWelcome to the future of documents, a series that helps you make the most of\nyour unstructured data with Document AI. There's an enormous amount of data\nin the documents we interact with, such as PDFs and emails, that contain unstructured\nor *dark* data. Join us for this series, where we show how you can\nuse this data to automate processes, gather analytics, and more.\n\n[Document AI Introductory codelab code](https://goo.gle/3OVnmnO)\n\nHow to use Document AI\n----------------------\n\nWant to learn how to use Document AI? This video shows how you can get started\nwith Document AI using the Google Cloud console or with the API using the python\nclient library. Watch to learn about Document AI processors, and see how you\ncan create your own.\n\n[Document AI Introductory codelab code](https://goo.gle/3OVnmnO)\n\n[Document AI processor management codelab code](https://goo.gle/3RqiWGJ)\n\nGeneral processors in Document AI\n---------------------------------\n\nIn this video, we take a deep dive into general processors. These are pre-trained\nand ready-to-use models designed to work on any document. Watch along and learn\nhow to get detailed structured information from documents with general processors\nin Document AI.\n\n[Document AI OCR codelab code](https://goo.gle/3oiqC0F)\n\n[Document AI form parsing codelab code](https://goo.gle/3PHROl4)\n\nSpecialized processors in Document AI\n-------------------------------------\n\nIn the previous episode, we discussed general processors in Document AI for most\ndocuments. However, did you know that there are more specialized processors for\ndocuments such as invoices, tax documents, and identification cards? In this episode,\nwe discuss how to use Document AI for: bank statements, W2s, US passports, utility bills,\nID proofing, paystubs, US driver's licenses, expenses, and invoices.\n\n[Document AI Specialized Processors Codelab code](https://goo.gle/3dk025d)\n\nDocument AI Workbench\n---------------------\n\nPreviously, we looked at Document AI specialized processors and how they can\nprovide intelligent insights into certain document types by providing consistent\nschemas and normalizing data to reduce the amount of pre/post-processing you need\nto perform. [Document AI Workbench](/document-ai/docs/workbench/training-overview) allows\nup-training of pre-trained processors and creating custom processors\nfrom scratch, without machine learning expertise.\n\n[Document AI Workbench: Uptraining Guidecode](/document-ai/docs/workbench/uptrain-processor)\n\n[Document AI Workbench: Custom Document Extractor Guidecode](/document-ai/docs/workbench/build-custom-processor)\n\n[Document AI Workbench: Custom Document Classifier Guidecode](/document-ai/docs/workbench/build-custom-classification-processor)\n\n[Document AI Workbench: Custom Document Splitter Guidecode](/document-ai/docs/workbench/build-custom-splitter-processor)"]]