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sathi akter
Aug 03, 2022
In Welcome to the Forum
Industry or the size of the enterprise, it is possible to combine with AI technology to create more unexpected and convenient services. How can we not be in it? Step up to keep up? Join the AWS Proof-of-Concept (POC) program today and move toward a human-centric technology of the future! Diversified cloud tools create low-threshold AI technology applications in various industries In fact, the key to the popularization of AI technology is not only the maturity of technology and the Update and iteration of information hardware, but also the bulk sms service emergence of "technology translation service" providers such as AWS Taiwan. AWS provides cloud-based tools with various functions, which greatly reduces the threshold for AI technology to start and use, and allows machine learning (ML) to penetrate into various industrial processes and achieve true popularization. Enterprises such as Discovery, 3M, Lalamove, and Subway restaurant chain (SUBWAY) have begun to use the following cloud tools provided by AWS to further optimize their products or services: Low barriers to entry, easy to use, and accurate ML predictions without programming: Amazon SageMaker Canvas simplifies the complex programming process of the past with a visual point-and-click interface, allowing Users to upload data, train models, and perform predictions without ML experience. Accelerates the creation of instant personalized user experiences at scale: Amazon Personalize does not require ML expertise, allowing developers to easily build instant personalized recommendations to provide optimal computing services to customers in industries such as retail, media and entertainment. Automatically capture printed, handwritten, and data: Amazon Textract uses optical character recognition to read and process any type of document using ML, accurately capture text, handwriting, forms, and other data without any manual effort . Execute and scale big data workloads with ease: Amazon EMR uses open source analytics frameworks such as Apache Spark, Apache Hive, and Presto to run large-scale distributed data
Technological era of nationalization of machine learning​, no matter the type of content media
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sathi akter

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