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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]
In 2021, Song was named a Fellow of the Institute of Mathematical Statistics, "for significant contributions to machine learning methods, dynamic treatment regime, and efficient and non-standard statistical inference". [3] In the same year she was also named a Fellow of the American Statistical Association. [4]
// comments are allowed in Ion files using the double forward slash {key: "value", // key here is a symbol, it can also be a string as in JSON nums: 1 _000_000, // equivalent to 1000000, use of underscores with numbers is more readable 'A float value': 31415e-4, // key is a value that contains spaces "An int value":. int, annotated: age:: 35, // age here is the annotation to number 35 lists ...
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 ]
AWS announces a new machine learning platform at the AWS Summit in San Francisco, specifically suited to machine learning without requiring specific expertise. [100] 2015: April 28: Acquisitions: AWS acquires ClusterK, a startup that allows users to run apps on Amazon's cloud for 1/10th of the regular price. [101] 2015: May 19: Evaluation
Furthermore, researchers involved in exploring learning algorithms for neural networks are gradually uncovering generic principles that allow a learning machine to be successful. For example, Bengio and LeCun (2007) wrote an article regarding local vs non-local learning, as well as shallow vs deep architecture. [231]
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