Plato Data Intelligence.
Vertical Search & Ai.

Tag: Amazon SageMaker Canvas

Supercharge your AI team with Amazon SageMaker Studio: A comprehensive view of Deutsche Bahn’s AI platform transformation | Amazon Web Services

AI’s growing influence in large organizations brings crucial challenges in managing AI platforms. These include developing a scalable and operationally efficient platform that adheres...

Top News

Overcoming common contact center challenges with generative AI and Amazon SageMaker Canvas | Amazon Web Services

Great customer experience provides a competitive edge and helps create brand differentiation. As per the Forrester report, The State Of Customer Obsession, 2022, being...

Accelerating time-to-insight with MongoDB time series collections and Amazon SageMaker Canvas | Amazon Web Services

This is a guest post co-written with Babu Srinivasan from MongoDB. As industries evolve in today’s fast-paced business landscape, the inability to have real-time...

Use Amazon DocumentDB to build no-code machine learning solutions in Amazon SageMaker Canvas | Amazon Web Services

We are excited to announce the launch of Amazon DocumentDB (with MongoDB compatibility) integration with Amazon SageMaker Canvas, allowing Amazon DocumentDB customers to build...

Boosting developer productivity: How Deloitte uses Amazon SageMaker Canvas for no-code/low-code machine learning | Amazon Web Services

The ability to quickly build and deploy machine learning (ML) models is becoming increasingly important in today’s data-driven world. However, building ML models requires...

Build and evaluate machine learning models with advanced configurations using the SageMaker Canvas model leaderboard | Amazon Web Services

Amazon SageMaker Canvas is a no-code workspace that enables analysts and citizen data scientists to generate accurate machine learning (ML) predictions for their business...

Accelerate data preparation for ML in Amazon SageMaker Canvas | Amazon Web Services

Data preparation is a crucial step in any machine learning (ML) workflow, yet it often involves tedious and time-consuming tasks. Amazon SageMaker Canvas now...

Simplify data prep for generative AI with Amazon SageMaker Data Wrangler | Amazon Web Services

Generative artificial intelligence (generative AI) models have demonstrated impressive capabilities in generating high-quality text, images, and other content. However, these models require massive amounts...

Democratize ML on Salesforce Data Cloud with no-code Amazon SageMaker Canvas | Amazon Web Services

This post is co-authored by Daryl Martis, Director of Product, Salesforce Einstein AI. This is the third post in a series discussing the integration...

Optimizing costs for Amazon SageMaker Canvas with automatic shutdown of idle apps | Amazon Web Services

Amazon SageMaker Canvas is a rich, no-code Machine Learning (ML) and Generative AI workspace that has allowed customers all over the world to more...

Use foundation models to improve model accuracy with Amazon SageMaker | Amazon Web Services

Photo by Scott Webb on Unsplash Determining the value of housing is a classic example of using machine learning (ML). A...

Use machine learning without writing a single line of code with Amazon SageMaker Canvas | Amazon Web Services

In the recent past, using machine learning (ML) to make predictions, especially for data in the form of text and images, required extensive ML...

Deploy ML models built in Amazon SageMaker Canvas to Amazon SageMaker real-time endpoints | Amazon Web Services

Amazon SageMaker Canvas now supports deploying machine learning (ML) models to real-time inferencing endpoints, allowing you take your ML models to production and drive...

Latest Intelligence

spot_img
spot_img
spot_img