New features for Amazon SageMaker Pipelines and the Amazon SageMaker SDK

Amazon SageMaker Pipelines allows data scientists and machine learning (ML) engineers to automate training workflows, which helps you create a repeatable process to orchestrate model development steps for rapid experimentation and model retraining. You can automate the entire model build workflow, including data preparation, feature engineering, model training, model tuning,

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Shared by AWS Machine Learning September 28, 2022

Provision and manage ML environments with Amazon SageMaker Canvas using AWS CDK and AWS Service Catalog

The proliferation of machine learning (ML) across a wide range of use cases is becoming prevalent in every industry. However, this outpaces the increase in the number of ML practitioners who have traditionally been responsible for implementing these technical solutions to realize business outcomes. In today’s enterprise, there is a

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Shared by AWS Machine Learning September 28, 2022

Build an AI-powered virtual agent for Genesys Cloud using QnABot and Amazon Lex

The rise of artificial intelligence technologies enables organizations to adopt and improve self-service capabilities in contact center operations to create a more proactive, timely, and effective customer experience. Voice bots, or conversational interactive voice response systems (IVR), use natural language processing (NLP) to understand customers’ questions and provide relevant answers.

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Shared by AWS Machine Learning September 28, 2022

Raising funds for a good cause while learning about Open Source trends

The second annual collaborative surve and report on the state of Open Source software, with OpenLogic and OSI. The post Raising funds for a good cause while learning about Open Source trends first appeared on Voices of Open Source. Click Here to View Original Source (opensource.org)

Quantization for Fast and Environmentally Sustainable Reinforcement Learning

Posted by Srivatsan Krishnan, Student Researcher, and Aleksandra Faust, Senior Staff Research Scientist, Google Research, Brain Team Deep reinforcement learning (RL) continues to make great strides in solving real-world sequential decision-making problems such as balloon navigation, nuclear physics, robotics, and games. Despite its promise, one of its limiting factors is

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Shared by Google AI Technology September 27, 2022