Amazon SageMaker Canvas

Build highly accurate ML models using a visual interface, no code required

Why SageMaker Canvas?

Through a no-code interface, you can create highly accurate machine learning models —without any machine learning experience or writing a single line of code. SageMaker Canvas provides access to ready-to-use models including foundation models from Amazon Bedrock or Amazon SageMaker JumpStart or you can build your own custom ML model using AutoML powered by SageMaker AutoPilot. With SageMaker Canvas, you can use SageMaker Data Wrangler to easily access and import data from 50+ sources, prepare data using natural language and 300+ built-in transforms, build and train highly accurate models, generate predictions, and deploy models to production.

Ready-to-Use Models

Foundation Models

SageMaker Canvas provides access to ready-to-use foundation model (FMs) such as Claude 2, Llama-2, Amazon Titan, Jurassic-2, and Command (powered by Amazon Bedrock) as well as publicly available FMs such as Falcon, Flan-T5, Mistral, Dolly, and MPT (powered by SageMaker JumpStart)

Foundation Models

Tabular, CV, and NLP models

SageMaker Canvas provides access to ready to use tabular, NLP, and CV models powered by AWS AI services, including Amazon Rekognition, Amazon Textract, and Amazon Comprehend.

Tabular, CV, and NLP models

Custom Models

Data Preparation

SageMaker Canvas offers no-code data exploration and preparation through a point-and-click or natural language UI powered by SageMaker Data Wrangler.

Data preparation

Build Models

SageMaker Canvas uses Amazon’s AutoML powered by SageMaker AutoPilot to build a custom model trained on your dataset.

Build Models

Evaluate Models

SageMaker Canvas helps you understand model performance with common evaluation metrics and visuals.

Evaluate Models

Use Models

You can generate predictions in the SageMaker Canvas UI or deploy to a SageMaker endpoint.

Use Models

Benefits of SageMaker Canvas

Amazon SageMaker Canvas provides a visual point-and-click interface for business analysts to solve business problems using ML such as customer churn prediction, fraud detection, forecasting financial metrics and sales, inventory optimization, content generation, and more without writing any code.