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Amazon SageMaker AI is a cloud-based machine-learning platform that allows the creation, training, and deployment by developers of machine-learning (ML) models on the cloud. [1] It can be used to deploy ML models on embedded systems and edge-devices. [2] [3] The platform was launched in November 2017. [4]
Amazon Kinesis is a family of services provided by Amazon Web Services (AWS) for processing and analyzing real-time streaming data at a large scale. Launched in November 2013, it offers developers the ability to build applications that can consume and process data from multiple sources simultaneously. [2]
Machine learning (ML) is a field of study in artificial intelligence concerned with the development and study of statistical algorithms that can learn from data and generalize to unseen data, and thus perform tasks without explicit instructions. [1]
TensorFlow serves as a core platform and library for machine learning. TensorFlow's APIs use Keras to allow users to make their own machine-learning models. [33] [43] In addition to building and training their model, TensorFlow can also help load the data to train the model, and deploy it using TensorFlow Serving. [44]
Machine learning (ML) is a subfield of artificial intelligence within computer science that evolved from the study of pattern recognition and computational learning theory. [1] In 1959, Arthur Samuel defined machine learning as a "field of study that gives computers the ability to learn without being explicitly programmed". [ 2 ]
Amazon Mechanical Turk (MTurk) is a crowdsourcing website with which businesses can hire remotely located "crowdworkers" to perform discrete on-demand tasks that computers are currently unable to do as economically. It is operated under Amazon Web Services, and is owned by Amazon. [1]
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