Notes:
Amazon SageMaker is a machine learning platform offered by Amazon Web Services (AWS) that allows users to build, train, and deploy machine learning models. It provides a range of tools and services that make it easier to build, train, and deploy machine learning models, including algorithms, pre-built machine learning models, and an integrated development environment (IDE) for building custom models.
One potential use of Amazon SageMaker in dialog systems is to train machine learning models that can be used to generate responses to user input. These models could be trained on large collections of dialog data to learn the patterns and structures of natural language, and then be used to generate appropriate responses to user input in real time.
Another potential use of Amazon SageMaker in dialog systems is to build and train machine learning models that can be used to classify user input and identify the intent behind it. This could be used to help a dialog system understand what the user is trying to accomplish, and to provide appropriate responses or take appropriate actions based on that intent.
Overall, Amazon SageMaker provides a range of tools and services that can be used to build and train machine learning models for use in dialog systems, making it easier to create sophisticated and effective natural language processing systems.
Resources:
- aws.amazon.com/sagemaker .. build, train, and deploy machine learning
References:
- Piloting Amazon SageMaker Made Easy (20 Feb 2019)
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- iMerit to offer secure enterprise-grade data labeling with Amazon … (5 Feb 2019)
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- Amazon open-sources SageMaker Neo to help developers optimize … (28 Jan 2019)
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- AWS open sources SageMaker Neo code as Neo-AI project (24 Jan 2019)
- A How To Course on edX About Amazon SageMaker and Machine … (25 Dec 2018)
- Amazon updates SageMaker with new built-in algorithms and Git … (10 Dec 2018)
- How the NFL is able to predict pass completion using AWS SageMaker (30 Nov 2018)
- Amazon SageMaker updates take on workflows, data labeling (29 Nov 2018)
- Reward your Machine mind’s little successes with AWS SageMaker RL (29 Nov 2018)
- DimensionalMechanics, Inc. Launches NeoPulse Framework on … (28 Nov 2018)
- Amazon launches AWS SageMaker Ground Truth, an automated data … (28 Nov 2018)
- Amazon launches an automated labeling service for its SageMaker … (28 Nov 2018)
- Qubole Unveils Cloud-Native Solution Leveraging Amazon … (27 Nov 2018)
- Machine learning for novices: AWS SageMaker update brings new … (23 Nov 2018)
- AWS boosts SageMaker with new AI algorithms, more automation (21 Nov 2018)
- Amazon adds new features to SageMaker (21 Nov 2018)
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- Periscope Data In Collaboration With SageMaker (19 Jul 2018)
- Accessible AI: With SageMaker, Amazon aims to bring machine … (18 Jul 2018)
- AWS SageMaker Upgrades Again (18 Jul 2018)
- AWS adds BYO streaming algorithms to SageMaker machine learning … (17 Jul 2018)
- Periscope Data integrates with Amazon’s SageMaker to simplify … (16 Jul 2018)
- Review: Amazon SageMaker scales deep learning (14 May 2018)
- Amazon Web Services adds new features to SageMaker and makes … (4 Apr 2018)
- AWS announces SageMaker Local Mode for building AI locally (4 Apr 2018)
- Amazon SageMaker goes for “Infinitely Scalable” Machine Learning (23 Mar 2018)
- Amazon Web Services reveals more details on the thinking behind … (19 Mar 2018)
- Amazon pulls back the curtain on SageMaker AI service (19 Mar 2018)
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- AWS Summit Anaheim 2018 – Working with ML in Amazon SageMaker (BDA203)
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