DeepLearning.AI, Coursera, and AWS launch the new Practical Data Science Specialization with Amazon SageMaker

Amazon Web Services (AWS), Coursera, and DeepLearning.AI are excited to announce Practical Data Science, a three-course, 10-week, hands-on specialization designed for data professionals to quickly learn the essentials of machine learning (ML) in the AWS Cloud. DeepLearning.AI was founded in 2017 by Andrew Ng, an ML and education pioneer, to

Read More
Shared by AWS Machine Learning June 2, 2021

Build reusable, serverless inference functions for your Amazon SageMaker models using AWS Lambda layers and containers

In AWS, you can host a trained model multiple ways, such as via Amazon SageMaker deployment, deploying to an Amazon Elastic Compute Cloud (Amazon EC2) instance (running a Flask + NGINX, for example), AWS Fargate, Amazon Elastic Kubernetes Service (Amazon EKS), or AWS Lambda. SageMaker provides convenient model hosting services

Read More
Shared by AWS Machine Learning June 1, 2021

Use Amazon Translate in Amazon SageMaker Notebooks

Amazon Translate is a neural machine translation service that delivers fast, high-quality, and affordable language translation in 71 languages and 4,970 language pairs. Amazon Translate is great for performing batch translation when you have large quantities of pre-existing text to translate and real-time translation when you want to deliver on-demand

Read More
Shared by AWS Machine Learning June 1, 2021

Where is the best place to store knowledge?

Where should knowledge be stored? There are many answers to this question!  A common answer is to say that knowledge should be stored in people’s heads, and some would argue that knowledge exists ONLY in human heads. That’s not an argument I want to get into, and for the sake

Read More
Shared by Nick Milton June 1, 2021

Host multiple TensorFlow computer vision models using Amazon SageMaker multi-model endpoints

Amazon SageMaker helps data scientists and developers prepare, build, train, and deploy high-quality machine learning (ML) models quickly by bringing together a broad set of capabilities purpose-built for ML. SageMaker accelerates innovation within your organization by providing purpose-built tools for every step of ML development, including labeling, data preparation, feature

Read More
Shared by AWS Machine Learning May 26, 2021

How Contentsquare reduced TensorFlow inference latency with TensorFlow Serving on Amazon SageMaker

In this post, we present the results of a model serving experiment made by Contentsquare scientists with an innovative DL model trained to analyze HTML documents. We show how the Amazon SageMaker TensorFlow Serving solution helped Contentsquare address several serving challenges. Contentsquare’s challenge Contentsquare is a fast-growing French technology company

Read More
Shared by AWS Machine Learning May 26, 2021