Enhance your SaaS offering with a data science workbench powered by Amazon SageMaker Studio

Favorite Many software as a service (SaaS) providers across various industries are adding machine learning (ML) and artificial intelligence (AI) capabilities to their SaaS offerings to address use cases like personalized product recommendation, fraud detection, and accurate demand protection. Some SaaS providers want to build such ML and AI capabilities

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Shared by AWS Machine Learning March 11, 2022

Build, Share, Deploy: how business analysts and data scientists achieve faster time-to-market using no-code ML and Amazon SageMaker Canvas

Favorite Machine learning (ML) helps organizations increase revenue, drive business growth, and reduce cost by optimizing core business functions across multiple verticals, such as demand forecasting, credit scoring, pricing, predicting customer churn, identifying next best offers, predicting late shipments, and improving manufacturing quality. Traditional ML development cycles take months and

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Shared by AWS Machine Learning March 11, 2022

Transforming qualitative research by automating speech to text-to-text analytics

Favorite This post is authored by Satish Jha, Intelligent Automation Manager, Matt Docherty, Data Science Manager, Jayesh Muley, Associate Consultant and Tapan Vora, Rapid Prototyping, from ZS Associates. At ZS Associates, we do a significant amount of qualitative market research. The work involves interviewing relevant subjects (such as healthcare professionals

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Shared by AWS Machine Learning March 10, 2022

Amazon SageMaker Autopilot now supports time series data

Favorite Amazon SageMaker Autopilot automatically builds, trains, and tunes the best machine learning (ML) models based on your data, while allowing you to maintain full control and visibility. We have recently announced support for time series data in Autopilot. You can use Autopilot to tackle regression and classification tasks on

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Shared by AWS Machine Learning March 10, 2022

Focus your KM first steps.

Favorite To start with, you don’t need Knowledge Management to be applied everywhere – only in the few places where it makes a difference. FOCUSR by Libertarian Girl on Flickr There is always a balance to be struck between burden and value. KM involves extra work – it involves attention

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Shared by Nick Milton March 7, 2022