Favorite Building a highly accurate training dataset for your machine learning (ML) algorithm is an iterative process. It is common to review and continuously adjust your labels until you are satisfied that the labels accurately represent the ground truth, or what is directly observable in the real world. ML practitioners

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Shared by AWS Machine Learning October 10, 2019

Favorite Ever been stumped by a question? Imagine you’re in a business review going over weekly numbers and someone asks, “What about expenses?” Your response might be, “I don’t know. I wasn’t prepared to have that discussion right now.” Bots aren’t fortunate enough to have the same comprehension capabilities, so

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Shared by AWS Machine Learning October 4, 2019

Favorite Amazon Textract is a machine learning service that makes it easy to extract text and data from virtually any document. Textract goes beyond simple optical character recognition (OCR) to also identify the contents of fields in forms and information stored in tables. This allows you to use Amazon Textract

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Shared by AWS Machine Learning October 3, 2019

Favorite Amazon Transcribe is an automatic speech recognition (ASR) service that makes it easy for developers to add speech-to-text capability to applications. In November 2018, we added streaming transcriptions over HTTP/2 to Amazon Transcribe. This enabled users to pass a live audio stream to our service and, in return, receive

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Shared by AWS Machine Learning September 28, 2019

Favorite AWS offers a vast array of services that allow developers to build applications in the cloud. At the same time, Windows desktop applications can take advantage of these services as well. Today, we are releasing Amazon Polly for Windows, an open-source engine that allows users to take advantage of

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Shared by AWS Machine Learning September 27, 2019

Favorite Machine learning (ML) is one of the fastest growing areas in technology and a highly sought after skillset in today’s job market. Today, I am excited to announce a new education course, built in collaboration with Coursera, to help you build your ML skills: Getting started with AWS Machine

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Shared by AWS Machine Learning September 19, 2019

Favorite Amazon SageMaker is a fully managed platform that enables developers and data scientists to quickly and easily build, train, and deploy machine learning (ML) models at any scale. When you deploy an ML model, Amazon SageMaker leverages ML hosting instances to host the model and provides an API endpoint

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Shared by AWS Machine Learning September 18, 2019

Favorite Optimization is the process of finding the minimum (or maximum) of a function that depends on some inputs, called design variables. Customer X has the following problem: They are about to release a new car model to be designed for maximum fuel efficiency. In reality, thousands of parameters that

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Shared by AWS Machine Learning September 17, 2019

Favorite Creating a global footprint and access to scale are one of the many best practices at AWS. By creating architectures that take advantage of that scale and also efficient data utilization (in both performance and cost), you can start to see how important access is at scale. For example, within autonomous

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Shared by AWS Machine Learning September 17, 2019

Favorite Amazon SageMaker supports all the popular deep learning frameworks, including TensorFlow. Over 85% of TensorFlow projects in the cloud run on AWS. Many of these projects already run in Amazon SageMaker. This is due to the many conveniences Amazon SageMaker provides for TensorFlow model hosting and training, including fully

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Shared by AWS Machine Learning September 13, 2019