최신 UiPath-SAIv1 무료덤프 - UiPath Certified Professional Specialized AI Professional v1.0

A. Create Labeling Action activity

B. Create Labeling Task activity

C. Create External Task activity

D. Create Document Labeling Action activity

A. Use the "Low confidence" training mode to pin the label to more communications.

B. Use the "Rebalance" training mode to pin the label to more communications.

C. Use the 'Teach" training mode to pin the label to more communications.

D. Use the "Search" feature to pin the label to more communications.

A. It allows training document extractors without manually creating Datasets and Pipelines, but you need to manually deploy the ML Skills in AI Center.

B. It provides a simplified way to manually create Datasets, Pipelines, and Datasets for document extraction.

C. It automates the creation of document extractors by automatically creating Datasets, Pipelines, and ML Skills but requires manual creation of Pipelines.

D. It allows training document extractors without manually creating Datasets, Pipelines, and ML Skills in AI Center.

A. If you import a schema into a document type that already contains a schema, the import will be successful and the schema will be overridden.

B. If you import a schema into a document type that already contains a schema, the import will be successful and the schema will be updated with the missing field.

C. If you import a schema into a document type that already contains a schema, the import will fail only if documents were already uploaded.

D. If you import a schema into a document type that already contains a schema, the import will fail.

A. The main reason is that all taxonomy fields should have their names translated into all the languages presented in the documents to be processed.

B. Different Document Understanding components have support for different languages, so they have to be selected according to the requirements.

C. If an ML (Machine Learning) extractor is used, the model schema fields should be renamed according to the most frequently used language from the documents to be processed

D. This is a standard check but has no actual effect on the Document Understanding process.

A. Document Manager.

B. Data Manager.

C. Digitization.

D. ML Extractor.

A. Dashboard. Datasets, Data Labeling. ML Packages. Pipelines, ML Skills, and ML Logs.

B. Datasets, Data Labeling. ML Packages, ML Training, ML Evaluation, ML Skills, and ML Logs.

C. Datasets. Data Labeling. ML Packages. Pipelines, and ML Skills.

D. Dashboard. Datasets. ML Packages. ML Training. ML Evaluation, and ML Logs.

A. 7 documents for training the model, and 8 for evaluating the model.

B. 10 documents for training the model, and 5 for evaluating the model.

C. 8 documents for training the model, and 7 for evaluating the model.

D. 12 documents for training the model, and 3 for evaluating the model.

A. The number of occurrences and the extraction confidence.

B. The page number from which the field was extracted and the exact position on the page.

C. The extraction confidence and the digitization confidence.

D. The position on the page.

A. Monitor model performance and receive recommendations.

B. View, save, and modify dataset model versions.

C. Train models using unsupervised learning.

D. Access detailed, quervable charts, statistics, and customizable dashboards.

A. Grouping as many document types under the same taxonomy as possible.

B. Designing taxonomies without considering the need for post-processing rules.

C. Focusing on creating separate taxonomies for each document type to avoid confusion.

D. Creating taxonomies that focus solely on scanned documents.