AWS Machine Learning Blog

Tag: Amazon Sagemaker

Run SQL queries from your SageMaker notebooks using Amazon Athena

The volume, velocity and variety of data has been ever increasing since the advent of the internet. The problem many enterprises face is managing this “big data” and trying to make sense out of it to yield the most desirable outcome. Siloes in enterprises, continuous ingestion of data in numerous formats, and the ever-changing technology […]

Read More

Transfer learning for custom labels using a TensorFlow container and “bring your own algorithm” in Amazon SageMaker

Data scientists and developers can use the Amazon SageMaker fully managed machine learning service to build and train machine learning (ML) models, and then directly deploy them into a production-ready hosted environment. In this blog post we’ll show you  how to use Amazon SageMaker to do transfer learning using a TensorFlow container with our own […]

Read More

Call an Amazon SageMaker model endpoint using Amazon API Gateway and AWS Lambda

At AWS Machine Learning workshops, customers often ask, “After I deploy an endpoint, where do I go from there?” You can deploy an Amazon SageMaker trained and validated machine learning model as an endpoint in production. Alternatively, you can choose which Amazon SageMaker functionality to use. For example, you could choose just to train a […]

Read More

Enhanced text classification and word vectors using Amazon SageMaker BlazingText

Today, we are launching several new features for the Amazon SageMaker BlazingText algorithm. Many downstream natural language processing (NLP) tasks like sentiment analysis, named entity recognition, and machine translation require the text data to be converted into real-valued vectors. Customers have been using BlazingText’s highly optimized implementation of the Word2Vec algorithm, for learning these vectors from […]

Read More

Object Detection algorithm now available in Amazon SageMaker

Amazon SageMaker is a fully-managed and highly scalable machine learning (ML) platform that makes it easy build, train, and deploy machine learning models. This is a giant step towards the democratization of ML and in lowering the bar for entry in to the ML space for developers. Computer vision is the branch of machine learning […]

Read More

Build multiclass classifiers with Amazon SageMaker linear learner

Amazon SageMaker is a fully managed service for scalable training and hosting of machine learning models. We’re adding multiclass classification support to the linear learner algorithm in Amazon SageMaker. Linear learner already provides convenient APIs for linear models such as logistic regression for ad click prediction, fraud detection, or other classification problems, and linear regression […]

Read More

Amazon SageMaker DeepAR now supports missing values, categorical and time series features, and generalized frequencies

Today we are launching several new features for DeepAR in Amazon SageMaker. DeepAR is a supervised machine learning algorithm for time series prediction, or forecasting, that uses recurrent neural networks (RNNs) to produce probabilistic forecasts. Since its launch, the algorithm has been used for a variety of use cases. We are excited to give developers access to new […]

Read More

Amazon SageMaker supports kNN classification and regression

We’re excited to announce that starting today Amazon SageMaker supports a built-in k-Nearest-Neighbor (kNN) algorithm for solving classification and regression problems. kNN is a simple, interpretable, and surprisingly strong model for multi-class classification, ranking, and regression. Introduction to kNN The idea behind kNN is that similar data points should have the same class, at least […]

Read More

Discover Financial Services applies machine learning through a Robocar event powered by Amazon SageMaker

The Discover Financial Services (DFS) team members who attended AWS re:Invent agreed that the Robocar Rally was an extremely impactful experience. By participating in this hackathon, six members of Discover’s core team received hands-on experience using machine learning (ML) and deep learning on AWS. They had a blast and created lasting memories! Discover’s Cloud Center […]

Read More