Amazon SageMaker Canvas is a no-code environment that allows users to easily utilize machine learning (ML) models for various data types. It integrates with Amazon Comprehend for natural language processing tasks like sentiment analysis and entity recognition. It also integrates with Amazon Rekognition for image analysis, and Amazon Textract for document analysis. The ready-to-use solutions in SageMaker Canvas eliminate the need for coding and data engineering.
No-Code Machine Learning with Amazon SageMaker Canvas
In the past, using machine learning (ML) for making predictions required extensive ML knowledge and coding skills. Today, ML has become more accessible to any user who wants to generate business value. With Amazon SageMaker Canvas, middle managers can create predictions for various data types without writing code.
Text Data
SageMaker Canvas integrates seamlessly with Amazon Comprehend for natural language processing (NLP) tasks. You can perform sentiment analysis, language detection, entity recognition, and personal information detection without any coding or data engineering. The pre-trained NLP models of Amazon Comprehend can be easily used by providing text data and selecting the desired capability.
- Sentiment Analysis: Determine if the sentiment of the input text is positive, negative, mixed, or neutral.
- Entities Extraction: Automatically detect people, organizations, locations, dates, quantities, and other entities mentioned in the text.
- Language Detection: Identify the dominant language of the text.
- Personal Information Detection: Detect personally identifiable information (PII) entities like names, addresses, dates of birth, phone numbers, and email addresses.
Image Data
SageMaker Canvas integrates with Amazon Rekognition for computer vision capabilities. Middle managers can easily upload image datasets and use Amazon Rekognition to detect objects, scenes, and text in the images.
- Object Detection: Detect and label objects in an image.
- Text Detection: Extract text from images.
Document Data
SageMaker Canvas offers ready-to-use solutions powered by Amazon Textract for document understanding needs.
- Document Analysis: Extract raw text, forms, tables, and signatures from documents.
- Identity Document Analysis: Analyze personal identification cards, driver’s licenses, and similar forms of identification to extract information.
- Expense Analysis: Analyze expense documents like invoices and receipts to extract summary fields and line item fields.
- Document Queries: Ask questions about your documents and extract specific answers.
SageMaker Canvas provides a no-code environment to use ML with ease across various data types. The visual interface and integration with AWS services eliminate the need for coding and data engineering. Middle managers can leverage advanced ML techniques to generate insights from both structured and unstructured data using ready-to-use solutions. Try out SageMaker Canvas today to evolve your company with AI and stay competitive.
For more information, visit the Amazon SageMaker Canvas documentation.
About the Authors
Julia Ang is a Solutions Architect based in Singapore, supporting customers in Southeast Asia and beyond to use AI & ML in their businesses. Loke Jun Kai is a Specialist Solutions Architect for AI/ML based in Singapore, working with customers across ASEAN to architect machine learning solutions at scale in AWS.
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