AWS Machine Learning Blog

The following diagram illustrates this architecture.

Building algorithmic trading strategies with Amazon SageMaker

Financial institutions invest heavily to automate their decision-making for trading and portfolio management. In the US, the majority of trading volume is generated through algorithmic trading. [1] With cloud computing, vast amounts of historical data can be processed in real time and fed into sophisticated machine learning (ML) models. This allows market participants to discover […]

Bring your own model with Amazon SageMaker script mode

As the prevalence of machine learning (ML) and artificial intelligence (AI) grows, you need the best mechanisms to aid in the experimentation and development of your algorithms. You might begin with the several built-in algorithms in Amazon SageMaker that simply require you to point the algorithm at your data and start a SageMaker training job. […]

Detect manufacturing defects in real time using Amazon Lookout for Vision

In this post, we look at how we can automate the detection of anomalies in a manufactured product using Amazon Lookout for Vision. Using Amazon Lookout for Vision, you can notify operators in real time when defects are detected, provide dashboards for monitoring the workload, and get visual insights from the process for business users. […]

Automate car insurance claims processing with Autonet and Amazon Rekognition Custom Labels

There is nothing more exhilarating than getting the keys to your first car or driving off the lot with the car of your dreams. Sadly, that exhilaration can quickly fade to frustration when your car is damaged. Working through the phone calls, emails, and damage reports with your insurance provider can be a painstaking process. […]

Hyundai reduces ML model training time for autonomous driving models using Amazon SageMaker

Hyundai Motor Company, headquartered in Seoul, South Korea, is one of the largest car manufacturers in the world. They have been heavily investing human and material resources in the race to develop self-driving cars, also known as autonomous vehicles. One of the algorithms often used in autonomous driving is semantic segmentation, which is a task […]

Reduce computer vision inference latency using gRPC with TensorFlow serving on Amazon SageMaker

AWS customers are increasingly using computer vision (CV) models for improved efficiency and an enhanced user experience. For example, a live broadcast of sports can be processed in real time to detect specific events automatically and provide additional insights to viewers at low latency. Inventory inspection at large warehouses capture and process millions of images […]

How Daniel Wellington’s customer service department saved 99% on translation costs with Amazon Translate

This post is co-authored by Lezgin Bakircioglu, Innovation and Security Manager at Daniel Wellington. In their own words, “Daniel Wellington (DW) is a Swedish fashion brand founded in 2011. Since its inception, it has sold over 11 million watches and established itself as one of the fastest-growing and most coveted brands in the industry.” In […]

ML model explainability with Amazon SageMaker Clarify and the SKLearn pre-built container

Amazon SageMaker Clarify is a new machine learning (ML) feature that enables ML developers and data scientists to detect possible bias in their data and ML models and explain model predictions. It’s part of Amazon SageMaker, an end-to-end platform to build, train, and deploy your ML models. Clarify was made available at AWS re:Invent 2020. […]

Build accurate ML training datasets using point-in-time queries with Amazon SageMaker Feature Store and Apache Spark

This post is co-written with Raphey Holmes, Software Engineering Manager, and Jason Mackay, Principal Software Development Engineer, at GoDaddy. GoDaddy is the world’s largest services platform for entrepreneurs around the globe, empowering their worldwide community of over 20 million customers—and entrepreneurs everywhere—by giving them all the help and tools they need to grow online. GoDaddy […]

Create a large-scale video driving dataset with detailed attributes using Amazon SageMaker Ground Truth

Do you ever wonder what goes behind bringing various levels of autonomy to vehicles? What the vehicle sees (perception) and how the vehicle predicts the actions of different agents in the scene (behavior prediction) are the first two steps in autonomous systems. In order for these steps to be successful, large-scale driving datasets are key. […]