8/17/2023 0 Comments No code zero codeAzLha2tj6sĪWS’ no-code Canvas is a simple GUI for Amazon’s existing SageMaker AutoML capabilities, Torsten Volk, an analyst at Enterprise Management Associates (EMA), told The New Stack. It supports only CSV data coming from S3, Redshift, or Snowflake. It’s more of a competitor to Google Cloud AutoML Tables and DataRobot. SageMaker Canvas is not a visual designer like Azure ML designer. However, SageMaker Canvas appears to be limited to the use of CVS files, as astutely noticed by TNS correspondent and analyst Janakiram MSV. “In case I decide to integrate the model into an automated production system, the Amazon SageMaker Studio integration lets me share the model easily with other data scientists in my team.” “This quick feedback loop and intuitive UI allows me to use the ML model without having to write custom code,” Casalboni wrote. He showed how a new ML model is then created by selecting New model in the Models section. csv files with respective product and shipping data (ProductData.csv and ShippingData.csv) for 120 products and 10,000 shipping records by simply selecting Import and Upload. In a blog post, Alex Casalboni, a developer advocate at AWS, showed how it is possible to use the SageMaker Canvas interface to merge two. This is powerful automated machine learning technology to create models that enable business users and analysts to create predictions at the same high quality as data scientists.” “There is an emphasis is terminology and visualization that are already familiar to analysts and complements the data analysis tools that they’re already using. “Now business users and analysts can use SageMaker Canvas to generate highly accurate predictions using an intuitive easy to use interface without writing code and no ML experience,” Adam Selipsky, CEO at Amazon Web Services (AWS), said during the keynote leading off the event. Still, it does offer ML capabilities for model predictions with an interface was easy to manage as an Excel spreadsheet. SageMaker Canvas was designed for simplicity, although that could possibly limit its range of use. Low-code/No-Code for ML? Amazon SageMaker Canvas “enables users.to generate highly accurate ML predictions using a visual point and click interface with no coding required,” says #reinvent2021 /IrOmBnAIX6 With the graphical user interface, business users can simply merge files from data sources in the cloud or on-premises in order to generate predictions for deliveries of goods, for example. AWS says it allows business analysts to build ML models for predictions without having to know how to write code or have ML expertise. But in the case of AWS, the cloud service provider giant is touting its release of Amazon SageMaker Canvas specifically as a no-code for ML. What exactly low-code/no-code means often remains murky as the definition can change according to the source. AWS also introduced Amplify Studio for web-application development, a tool to cut (though not eliminate) the amount of code written for the AWS Amplify web development stack. Low-code/no-code underpinned some of Amazon Web Services’ (AWS) key announcements at its annual Re:Invent users conference in Las Vegas, including the availability of the no-code platform SageMaker Canvas for machine learning (ML).
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