Favorite Recommendation systems are one of the most widely adopted machine learning (ML) technologies in real-world applications, ranging from social networks to ecommerce platforms. Users of many online systems rely on recommendation systems to make new friendships, discover new music according to suggested music lists, or even make ecommerce purchase

Read More
Shared by AWS Machine Learning January 13, 2022

Favorite In deep learning, batch processing refers to feeding multiple inputs into a model. Although it’s essential during training, it can be very helpful to manage the cost and optimize throughput during inference time as well. Hardware accelerators are optimized for parallelism, and batching helps saturate the compute capacity and

Read More
Shared by AWS Machine Learning January 13, 2022

Favorite Cloud security at AWS is the highest priority. Amazon SageMaker Studio offers various mechanisms to protect your data and code using integration with AWS security services like AWS Identity and Access Management (IAM), AWS Key Management Service (AWS KMS), or network isolation with Amazon Virtual Private Cloud (Amazon VPC).

Read More
Shared by AWS Machine Learning January 12, 2022

Favorite This is the first in a two-part blog series on how Tyson Foods, Inc., is utilizing Amazon SageMaker and AWS Panorama to automate industrial processes at their meat packing plants by bringing the benefits of artificial intelligence applications at the edge. In part one, we discuss an inventory counting

Read More
Shared by AWS Machine Learning January 11, 2022

Favorite Cybersecurity continues to be a top concern for enterprises. Yet the constantly evolving threat landscape that they face makes it harder than ever to be confident in their cybersecurity protections. To address this, ReliaQuest built GreyMatter, an Open XDR-as-a-Service platform that brings together telemetry from any security and business solution, whether on-premises or in one

Read More
Shared by AWS Machine Learning January 10, 2022

Favorite This is a guest post by Jihye Park, a Data Scientist at MUSINSA.  MUSINSA is one of the largest online fashion platforms in South Korea, serving 8.4M customers and selling 6,000 fashion brands. Our monthly user traffic reaches 4M, and over 90% of our demographics consist of teens and

Read More
Shared by AWS Machine Learning January 10, 2022

Favorite With the advent of artificial intelligence (AI) and machine learning (ML), customers and the general public have become increasingly aware of their privacy, as well as the value that it holds in today’s data-driven world. Enterprises are actively seeking out and marketing privacy-first solutions, especially in the Computer Vision

Read More
Shared by AWS Machine Learning January 7, 2022

Favorite We’re living in a world of everything-as-an-online-service. Service providers from almost every industry are in the race to feature the best user experience for their online channels like web portals and mobile applications. This raises a new challenge. How do we stop illegal and fraudulent behaviors without impacting typical

Read More
Shared by AWS Machine Learning January 5, 2022

Favorite Amazon SageMaker Serverless Inference (Preview) was recently announced at re:Invent 2021 as a new model hosting feature that lets customers serve model predictions without having to explicitly provision compute instances or configure scaling policies to handle traffic variations. Serverless Inference is a new deployment capability that complements SageMaker’s existing

Read More
Shared by AWS Machine Learning January 5, 2022

Favorite In parts one and two of our guide to conversation design with Amazon Lex, we discussed how to gather requirements for your conversational AI application and draft conversational flows. In this post, we help you bring all the pieces together. You’ll learn how draft an interaction model to deliver

Read More
Shared by AWS Machine Learning January 5, 2022