During Email automation when executing I get windows security problem how to fix it

Very informative, Thanks can i have the presentation slides via email?

Could you share deploy.yml file?

I am getting this error when the workflow is Building The Nuget Package: xdg-open: no method available for opening '/home/runner/work/CICDTest/CICDTest/Scripts/uipathcli/23.10.8753.32995/tools/uipcli.exe' Error: Process completed with exit code 1.

Insightful Session

Hello Sir, i am not able to find Ui Path public repository(Script) files. Please help in this

how can we explore in our test project?what access or applications are required? am using uipath test suite manager and uipath studio.could you please help me to explore this GenAi model

Where can I get those API files ? I am not able to generate token

Just a thought, I think it will be very helpful specially for new learners to get build series wise in Git (for a week the access is kept for something) with all decks and document steps to follow - this can help new learners initially understand how to work with test automation. Initially even looking at the code for this 1/2 test cases and integrations can be extremely helpful to understand in depth how and where to start for starters. Todays one was a great session and thanks to whole team for all the effort and support.

Where do i get the sample data for practice

Why is he still saying Studio PRO?!? That product is long gone. Is this an old video that you streamed recently?

I have tried the same way but the access token is not generating 🥲

How to get access of autopilot for generate apps on orchestrator?

Thank you, I already build this seeing other youtube videos but no one is demonstrating the Problem with Postman, there is an issue with Postman- Can you run the Postman and check the results validation - I have also posted in community forum and almost everyone is stuck with the same issue for Postman. If you can please do a Postman API session or just demo us the Postman Validation - it would be very helpful. Thanks!

Is there a first part of this where the code was fixed ? or any git hub link to see the full presentation ? Thank you!

When i export the emails into csv, i do not get 'Message id' and 'timestamp' column columns, can suggest how to get these two columns before uploading as data source.

Thanks for the great learning experience with real world business case.

Please share link for other courses as well sir .

Why is not the Connector Builder Scope available in Studio? Only UiPath.IntegrationService.Activities?

How do we pass variables to the Invoke Workday operation? I have been having a hard time converting the variable to the specific Workday data type

Does anyone know who to convert a string to a particular type of Workday variable. I have been having a hard passing variables through the Invoke activity

Congratulations, guys! You have put in great effort.

How do we get trail version for process mining ?

This stuff takes Document Understanding to a whole new level. Awesome job both Nisarg and Monica!

Nice Bro :)

Nice bro

Great 👍

This is a great session

Good job guys!

the noise is so annoying. please be more carefull

Hey what uipath studio version are you using? I don't see the generate option in 2023.4.4 version

Super intéressant !!! Estoy haciendo lo mismo que el vidéo en mi ambiente de UiPath y es génial !! Muchas gracias y sigan haciendo vidéo de este tema.

I'm using M365 scope, version 2.5.9 (latest as of today 9 Apr 2024), with "Properties Panel" method. The "Request API permissions" of the registered application are all under "Delegated permissions" (to access the API as the signed-in user). And all the APIs I selected are marked as No for "Admin consent required". Yet, when I tried to call the 365 APIs, e.g. to find folder in Onedrive, I was still redirected to the prompt to get Admin Approval to "UiPath New York" for a lot of extra rights, such as - Read user files - Read all files that user can access - Have full access to user files - Have full access to all files user can access - Read items in all site collections - Edit or delete items in all site collections - View users' basic profile This doesn't make any sense! And even if it requires Admin approval for all these rights, it should be stated in your documentation ("M365 Admin approval to UiPath New York for .... is mandatory" or something like that) but it's not. docs.uipath.com/activities/other/latest/productivity/microsoft-office-365-scope. And talking about the documentation, Azure AD has been renamed to "Entra ID" for quite a long time now. Clearly your documentation is not updated. I start to wonder do you really want people to use this package or not?

I also had the same question regarding SSO, do we have a way to use Single Sign-On with the UiPath Workday Connector or should it always be using username/password?

How to add release notes to a package is there any variable we can configure in yml file UiPath deploy step

Is there a stat on the growth of new UI Path related job openings vs companies having existing employees doing the training?

00:01 Document understanding simplifies processing various document types for more efficient RPA workflows. 02:28 Document understanding involves taxonomy, digitization, classification, and extraction. 07:10 Data extraction and retraining process 09:20 Introduction to Generative Classifier and Extractor 13:58 Action Center enables human validation of data and error fixing 16:16 Action Center is used when human involvement is needed for use cases. 20:35 Configuring input sources for document understanding 22:45 Configuring Google Drive account 26:54 Reusing variables in the studio platform for efficient workflow management 28:55 Reusing variables and extracting classification results 33:36 Validating the classification results 35:40 Introducing generative structure for classification 40:25 Configuring and extracting values using document understanding 42:56 Workflow execution and document classification 48:01 Execution and validation of document classification and data extraction process. 50:26 Demonstrating document classification and data extraction using Generative Classifier and Extractor 54:42 Maintain a list of mandatory fields for invoice processing. 56:35 Validate extracted data in document understanding process 1:01:12 Automated document classification and data extraction process 1:04:07 Document understanding and table data extraction 1:08:16 Efficiently building automations with data retrieval and action execution 1:10:29 Demonstration of printing line items data with generative capabilities 1:15:00 Understanding generator classifier and extractor functionalities 1:17:47 Encourage sharing and tagging on LinkedIn for user benefit

00:00 Document understanding is crucial for efficient processing of documents across various organizational departments. 02:17 Building an intelligent document processing solution in UiPath 06:32 Automating resolution of valid exceptions for document understanding. 08:27 Using insights to track operations and business value 12:42 Key value drivers impact document processing automation 14:50 Understanding and analyzing reasons for document rejection 19:50 Dimensions, table calculations, and measures are key metrics in building dashboards. 21:42 Building two essential dashboards for document processing use case. 25:19 Document understanding best practice and lessons learned 27:38 Introducing AI-powered document understanding for time-saving benefits 32:18 Introduced manual document understanding workflow with continuous improvement process 34:32 Document understanding solution overview 39:11 Intelligent document understanding utilizing OCRs, classifiers, and validation for accurate data extraction 41:32 Validating and processing data flow for document understanding 46:13 Box models provide automation modules for document processing 48:10 Dev Dives offers a range of valuable content throughout the year 52:47 Models within document understanding platform are not fine-tunable yet. 54:56 Utilizing purchase order AI model for processing varied document formats 59:09 Exploring AI-powered document understanding for legal documents processing 1:01:11 Integration with Microsoft Azure open AI service 1:05:00 Using document understanding service to build a training data set 1:07:07 Balancing and representing training data set for understanding document population 1:11:09 Offering personalized models for specific use cases and document populations

00:06 Model Training in Document Understanding 02:16 Model Training in Document Understanding 08:08 AI plays a crucial role in document processing by understanding, classifying, and extracting information. 10:58 Understanding document layout is crucial for AI document processing 16:32 Understanding language support & necessary modules in AI document processing 19:07 Data extraction and model training are crucial for Document Understanding 23:59 Key aspects in document understanding process 26:27 Training model for document understanding 31:34 Consider the model performance and data balance during model training. 34:19 Document Understanding service enables creation of customized document classifiers 39:34 Training AI models for specific document fields 42:09 Automatic document classification and training process 46:52 Models for document understanding 49:46 Creating and labeling document schema 55:23 Select minor version zero for training to avoid data limitations 58:03 Split multiple document types into separate files for training 1:03:22 Model training involves evaluation and fine-tuning for accuracy improvement 1:06:01 Training model for document classification 1:11:57 Automated model training and updating process 1:14:33 Generative extractor provides flexible field extraction options 1:20:51 Utilizing data properties for validation and export 1:23:28 Validations and verifications are crucial for ensuring the accuracy of extracted data 1:28:19 Document Understanding features OCR for handwritten data extraction 1:31:15 Consistency in logic writing and workflow for model training.

00:00 Document Understanding Framework combines Document Processing, RPA, and AI 02:07 Document Understanding Architecture combines different technologies to extract information from documents efficiently. 06:29 Different approaches in extracting information: rule-based and model-based. 08:28 Defining input variables and schema in Document Understanding Framework 12:40 Post-processing techniques are necessary for validation after machine-based classification and extraction. 15:08 Model accuracy varies for each document 19:27 UI Path uses ML skill to process and extract information from invoices 21:35 Implement post-processing logic for high confidence levels 25:58 Document Understanding Architecture includes ability to split and classify documents. 28:19 Using intelligent OCR to extract information from structured form documents 33:23 Defining field types and checking for tick marks 35:37 Checkbox selection and data extraction 39:55 Accessing and iterating through files in a folder 43:12 Configuring OCR options for PDF digitization 48:15 Document Understanding Architecture captures document information for classification and extraction 50:27 Document Understanding Architecture overview 55:53 Using intelligent keyword classifier for document classification 58:26 Classifying documents using a human-in-the-loop approach. 1:05:33 Document classification for multiple forms within a single document 1:08:13 Two ways of document classification: manual keyword classifier and intelligent keyword classifier 1:13:01 Creating templates for form-based documents 1:16:21 Configuring validation and extraction steps for document understanding 1:22:25 The final step in the Document Understanding Framework is the export process 1:24:54 Naming conventions for file exports and Excel sheets 1:29:46 Setting confidence thresholds for validation 1:32:26 Document Understanding Framework can handle multiple documents with classification results. 1:37:23 Updating template for classification in Document Understanding Framework 1:40:11 Different types of documents require different machine learning models for extraction 1:44:56 Document Understanding Framework enables automated labeling of fields for efficient data labeling process 1:47:05 Options for labeling data: Model Predict vs Generative Predict 1:51:30 Recommendation to go with base version as zero for retraining 1:53:41 Configuring ml skill for document extraction 1:59:56 Importance of defining classification fields in data labeling 2:02:07 Document Understanding Framework enables extraction rules 2:07:13 Expressing gratitude for participants

00:00 Today's focus is all about UiPath's document understanding product. 02:24 Specialized AI focuses on specific operations and tasks. 07:00 You can use this model as a pre-trained model. 09:09 Document Understanding provides various automation options 13:47 Automatic workflow creation from uploaded document 16:02 Streamlining document understanding with structured data extraction 20:28 DU framework offers multiple APIs for seamless automation 22:22 Understanding the process of Document Understanding automation 26:38 Different import types and features 28:24 Demonstration of document understanding and labeling process 32:50 Form zi simplifies document understanding model creation 35:11 Data labeling session setup for seamless automation 39:51 Automatic field prediction and labeling saves 80% labeling time. 41:44 Setting up and deploying ML packages in AI Center 45:51 ML skills can be used post pipeline completion 47:47 The DU framework simplifies document understanding 51:26 UIPath Academy provides comprehensive training on Document Understanding from scratch 53:28 AI in document understanding does not use OCR independently 57:20 Encouraging participants to open the shared links for registration.

00:03 AI Center enables AI capabilities in document understanding workflow. 00:48 AI Center is a great place for complex solutioning using document understanding 01:12 AI Center provides an ecosystem for ML model training, deployment, and retraining. 01:44 AI Center enables training, deployment, retraining, and evaluation of ML models. 02:24 Developing machine learning models in AI Center is easy for RPA developers 02:51 UiPath offers ML packages for various document types 03:21 Understanding model performance from a developer perspective. 03:52 Being an MVP offers a global perspective and fosters togetherness.

00:00 Introduction to Document Understanding and Framework 00:06 Introduction to Document Understanding and Document Understanding Framework 02:57 Overview of UAT Business Automation Platform 08:01 Document processing automation can improve efficiency, productivity, and data security. 10:55 Automating document processing with AI for accuracy and efficiency 16:08 Document understanding involves structured, semi-structured, and unstructured documents. 18:36 Document Understanding Framework involves text extraction, classification, validation, and retraining. 22:50 Document Understanding framework runs processes at the backend to digitize, classify, and validate documents. 25:03 Different approaches in document understanding: rules-based, AI-based, and hybrid 29:51 Document understanding framework allows creation of POC and demos for customers. 32:13 Document Understanding Framework enables understanding and processing of various document types. 36:55 Initialization process involves loading configuration file and initializing workflow 38:58 Document Understanding Framework involves setting API keys and classifying document types. 43:18 Document Understanding solution uses UIPath Document Understanding service with ML skills instead of endpoints 45:45 Robot sends data for validation and can perform additional actions while waiting for human input. 50:24 Using Document Understanding to assign tasks and classify documents for processing by the robot. 52:48 Humans play a crucial role in validating document understanding results. 57:12 Training a machine learning model for document understanding

solution accelerators are essential now

How you have created base URL for odata and provided access

Good going

DU Template is not covered in this long video

awesome explanation Mukesh. Hatsoff :)