AWS Machine Learning Blog
Category: Artificial Intelligence
Exploring data warehouse tables with machine learning and Amazon SageMaker notebooks
Are you a data scientist with data warehouse tables that you’d like to explore in your machine learning (ML) environment? If so, read on. In this post, I show you how to perform exploratory analysis on large datasets stored in your data warehouse and cataloged in your AWS Glue Data Catalog from your Amazon SageMaker […]
The AWS DeepRacer League virtual circuit is underway—win a trip to re:Invent 2019!
The competition is heating up in the AWS DeepRacer League, the world’s first global autonomous racing league, open to anyone. The first round is almost halfway home, now that 9 of the 21 stops on the summit circuit schedule are complete. Developers continue to build new machine learning skills and post winning times to the […]
Build end-to-end machine learning workflows with Amazon SageMaker and Apache Airflow
October 2021: Updating for airflow versions with MWAA supported releases, simplifying dependencies and adding Aurora Serverless as a DB option. In addition, new features (Session Manager integration and CloudFormation Stack status for the EC2 deployment) have been added. Machine learning (ML) workflows orchestrate and automate sequences of ML tasks by enabling data collection and transformation. […]
More ways to compete and win in the AWS DeepRacer League and two new champions!
It’s been a busy week for the AWS DeepRacer League. The world’s first global autonomous racing league allows machine learning developers of all skill levels to get hands-on with machine learning in a fun and exciting way. On April 29 2019, the virtual circuit of the AWS DeepRacer League opened. The virtual circuit allows racers […]
Build a custom data labeling workflow with Amazon SageMaker Ground Truth
Good machine learning models are built with large volumes of high-quality training data. But creating this kind of training data is expensive, complicated, and time-consuming. To help a model learn how to make the right decisions, you typically need a human to manually label the training data. Amazon SageMaker Ground Truth provides labeling workflows for […]
Amazon SageMaker Object2Vec adds new features that support automatic negative sampling and speed up training
Today, we introduce four new features of Amazon SageMaker Object2Vec: negative sampling, sparse gradient update, weight-sharing, and comparator operator customization. Amazon SageMaker Object2Vec is a general-purpose neural embedding algorithm. If you’re unfamiliar with Object2Vec, see the blog post Introduction to Amazon SageMaker Object2Vec, which provides a high-level overview of the algorithm with links to four notebook […]
End document drudgery with Alkymi’s AWS-powered automated data entry and document insights
Even in today’s highly digital workplace, documents are often manually processed in many enterprise workflows, including workflows in financial services. Alkymi, founded by a team from Bloomberg and x.ai, enlists automation to streamline this laborious and error-prone work. Using deep learning models hosted on Amazon SageMaker, Alkymi identifies patterns and relationships in unstructured data and […]
Running Java-based deep learning with MXNet and Amazon Elastic Inference
Note: Amazon Elastic Inference is no longer available. Please see Amazon SageMaker for similar capabilities. The new release of MXNet 1.4 for Amazon Elastic Inference now includes Java and Scala support. Apache MXNet is an open source deep learning framework used to build, train, and deploy deep neural networks. Amazon Elastic Inference (EI) is a […]
Udacity’s Machine Learning Nanodegree now includes Amazon SageMaker
During the past few years, the demand for machine learning specialists and engineers has soared. These two roles now rank among the top emerging jobs on LinkedIn. More recently, machine learning is being adopted by a wide range of industries, from medical diagnostic companies to finance firms and more. Udacity created the Intro to Machine […]
Use the wisdom of crowds with Amazon SageMaker Ground Truth to annotate data more accurately
Amazon SageMaker Ground Truth helps you quickly build highly accurate training datasets for machine learning (ML). To get your data labeled, you can use your own workers, a choice of vendor-managed workforces that specialize in data labeling, or a public workforce powered by Amazon Mechanical Turk. The public workforce is large and economical but as […]