AWS Machine Learning Blog

Machine learning for all developers with edX and Amazon SageMaker

Customers often ask us how to get started when they do not have a deep data science and machine learning (ML) background. At AWS, our goal is to put ML in the hands of every developer and data scientist. AWS Training and Certification has partnered with edX to help you get started quickly and easily with ML with […]

Creating custom labeling jobs with AWS Lambda and Amazon SageMaker Ground Truth  

Amazon SageMaker Ground Truth helps you build highly accurate training datasets for machine learning. It offers easy access to public and private human labelers, and provides them with built-in workflows and interfaces for common labeling tasks. Ground Truth can lower your labeling costs by up to 70% using automatic labeling. It works by training Ground […]

Digging deep and solving problems: Well Data Labs applies machine learning to oil and gas challenges

When CEO Josh Churlik co-founded Well Data Labs in 2014, he was acutely aware of a bizarre dichotomy in his industry: For oil and gas companies, “downhole” innovation (that is, what happens underground) far exceeds the pace of data and analysis innovation. The data systems used then were relics of the 1990s – more homages […]

Full ML Engineer scholarships from Udacity and the AWS DeepRacer Scholarship Challenge

The growth of artificial intelligence could create 58 million net new jobs in the next few years, states the World Economic Forum [1]. Yet, according to the Tencent Research Institute, it’s estimated that currently there are 300,000 AI engineers worldwide, but millions are needed [2]. As you can tell, there is a unique and immediate […]

Pricing housing just right: Entrata enables apartments to fill capacity with Amazon SageMaker and 1Strategy

The housing market is complex.  There is a continuously changing supply of student housing units around any given education campus. Moreover, the accepted value of a unit continuously changes based on physical and social variables. These variables could include proximity to campus with regard to other available options, friend groups living nearby, and the availability […]

Helping students learn with Course Hero, powered by Amazon SageMaker

Course Hero is an online learning platform that provides students access to over 25 million course-specific study materials, including study guides, class notes, and practice problems for numerous subjects. The platform, which runs on AWS, is designed to enable every student to take on their courses feeling confident and prepared. To make that possible, Course […]

Voicing play with Volley, where words are the gameboard and Amazon Polly brings the fun

Voice-powered experiences are gaining traction and customer love. Volley is at the cutting edge of voice-controlled entertainment with its series of popular smart-speaker games, and many aspects of Volley rely on Amazon Polly. Every day, more and more people switch on lights, check the weather, and play music not by pushing buttons but with verbal […]

Optimizing costs in Amazon Elastic Inference with TensorFlow

Amazon Elastic Inference allows you to attach low-cost GPU-powered acceleration to Amazon EC2 and Amazon SageMaker instances, and reduce the cost of running deep learning inference by up to 75 percent. The EIPredictorAPI makes it easy to use Elastic Inference. In this post, we use the EIPredictor and describe a step-by-step example for using TensorFlow with Elastic Inference. Additionally, we […]

Bring your own deep learning framework to Amazon SageMaker with Model Server for Apache MXNet

Deep learning (DL) frameworks enable machine learning (ML) practitioners to build and train ML models. However, the process of deploying ML models in production to serve predictions (also known as inferences) in real time is more complex. It requires that ML practitioners build a scalable and performant model server, which can host these models and […]