AWS Machine Learning Blog

JULY 29, 2024

In Part 3 , we demonstrate how business analysts and citizen data scientists can create machine learning (ML) models, without code, in Amazon SageMaker Canvas and deploy trained models for integration with Salesforce Einstein Studio to create powerful business applications.

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AWS Machine Learning Blog

SEPTEMBER 23, 2024

Launched in 2021, Amazon SageMaker Canvas is a visual point-and-click service that allows business analysts and citizen data scientists to use ready-to-use machine learning (ML) models and build custom ML models to generate accurate predictions without writing any code. This is crucial for compliance, security, and governance.

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AWS Machine Learning Blog

OCTOBER 10, 2023

Launched in 2021, Amazon SageMaker Canvas is a visual, point-and-click service that allows business analysts and citizen data scientists to use ready-to-use machine learning (ML) models and build custom ML models to generate accurate predictions without the need to write any code.

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DataRobot Blog

MARCH 28, 2022

DataRobot provides a Machine Learning platform that allows data scientists and citizen data scientists to quickly and efficiently prepare, build and evaluate many competing models in order to identify the optimal algorithm to solve the use case. AI Partners. Learn more. Learn More.

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AWS Machine Learning Blog

NOVEMBER 2, 2023

SageMaker Canvas is a no-code workspace that enables analysts and citizen data scientists to generate accurate ML predictions for their business needs. Always working backward from customer problems, Indy advises AWS enterprise customer executives through their unique cloud transformation journey.

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AWS Machine Learning Blog

NOVEMBER 27, 2023

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 of Salesforce Data Cloud and Amazon SageMaker. SageMaker endpoints can be registered to the Salesforce Data Cloud to activate predictions in Salesforce.

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Pickl AI

DECEMBER 4, 2024

Summary: The future of Data Science is shaped by emerging trends such as advanced AI and Machine Learning, augmented analytics, and automated processes. As industries increasingly rely on data-driven insights, ethical considerations regarding data privacy and bias mitigation will become paramount.

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