AWS Machine Learning Blog

Category: Artificial Intelligence

Your Guide to the AWS Machine Learning Summit

We’re about a week away from the AWS Machine Learning Summit and if you haven’t registered yet, you better get on it! On June 2, 2021 (Americas) and June 3, 2021 (Asia-Pacific, Japan, Europe, Middle East, and Africa), don’t miss the opportunity to hear from some of the brightest minds in machine learning (ML) at […]

Read More

It’s a wrap for Amazon SageMaker Month, 30 days of content, discussions, and news

Did you miss SageMaker Month? Don’t look any further than this round-up post to get caught up. In this post, we share key highlights and learning materials to accelerate your machine learning (ML) innovation. On April 20, 2021, we launched the first ever Amazon SageMaker Month, 30 days of hands-on workshops, tech talks, Twitch sessions, […]

Read More

Enhance sports narratives with natural language generation using Amazon SageMaker

This blog post was co-authored by Arbi Tamrazian, Director of Data Science and Machine Learning at Fox Sports. FOX Sports is the sports television arm of FOX Network. The company used machine learning (ML) and Amazon SageMaker to streamline the production of relevant in-game storylines for commentators to use during live broadcasts. “We collaborated with […]

Read More

How lekker got more insights into their customer churn model with Amazon SageMaker Debugger

With over 400,000 customers, lekker Energie GmbH is a leading supraregional provider of electricity and gas on the German energy market. lekker is customer and service oriented and regularly scores top marks in comparison tests. As one of the most important suppliers of green electricity to private households, the company, with its 220 employees, stands […]

Read More

Best practices in customer service automation

Chatbots, virtual assistants, and Interactive Voice Response (IVR) systems are key components of successful customer service strategies. We had the pleasure of hearing from three AWS Contact Center Intelligence (AWS CCI) Partners as part of our Best Practices in Customer Service Automation webinar, who provided valuable insights and tips for building automated, customer-service solutions. The […]

Read More

Implement live customer service chat with two-way translation, using Amazon Connect and Amazon Translate

Many businesses support customers across multiple countries and ethnic communities, and therefore need to provide customer service in a wide variety of local languages. It’s hard to consistently staff contact centers with agents with different language proficiencies. During periods of high call volumes, callers often must wait on hold for an agent who can speak […]

Read More

Reduce ML inference costs on Amazon SageMaker with hardware and software acceleration

Amazon SageMaker is a fully-managed service that enables data scientists and developers to build, train, and deploy machine learning (ML) models at 50% lower TCO than self-managed deployments on Elastic Compute Cloud (Amazon EC2). Elastic Inference is a capability of SageMaker that delivers 20% better performance for model inference than AWS Deep Learning Containers on […]

Read More

Automate feature engineering pipelines with Amazon SageMaker

The process of extracting, cleaning, manipulating, and encoding data from raw sources and preparing it to be consumed by machine learning (ML) algorithms is an important, expensive, and time-consuming part of data science. Managing these data pipelines for either training or inference is a challenge for data science teams, however, and can take valuable time […]

Read More

Learn how the winner of the AWS DeepComposer Chartbusters Keep Calm and Model On challenge used Transformer algorithms to create music

AWS is excited to announce the winner of the AWS DeepComposer Chartbusters Keep Calm and Model On challenge, Nari Koizumi. AWS DeepComposer gives developers a creative way to get started with machine learning (ML) by creating an original piece of music in collaboration with artificial intelligence (AI). In June 2020, we launched Chartbusters, a global […]

Read More

Speed up YOLOv4 inference to twice as fast on Amazon SageMaker

Machine learning (ML) models have been deployed successfully across a variety of use cases and industries, but due to the high computational complexity of recent ML models such as deep neural networks, inference deployments have been limited by performance and cost constraints. To add to the challenge, preparing a model for inference involves packaging the […]

Read More