AWS Machine Learning Blog

Category: Amazon Machine Learning

AWS ML Community showcase: March 2021 edition

In our Community Showcase, Amazon Web Services (AWS) highlights projects created by AWS Heroes and AWS Community Builders.  Each month AWS ML Heroes and AWS ML Community Builders bring to life projects and use cases for the full range of machine learning skills from beginner to expert through deep dive tutorials, podcasts, videos, and other […]

The following images show an example (left) where the model predicted every helmet correctly

Helmet detection error analysis in football videos using Amazon SageMaker

The National Football League (NFL) is America’s most popular sports league. Founded in 1920, the NFL developed the model for the successful modern sports league and is committed to advancing progress in the diagnosis, prevention, and treatment of sports-related injuries. Health and safety efforts include support for independent medical research and engineering advancements in addition […]

Explaining Bundesliga Match Facts xGoals using Amazon SageMaker Clarify

One of the most exciting AWS re:Invent 2020 announcements was a new Amazon SageMaker feature, purpose built to help detect bias in machine learning (ML) models and explain model predictions: Amazon SageMaker Clarify. In today’s world where predictions are made by ML algorithms at scale, it’s increasingly important for large tech organizations to be able […]

AI for AgriTech: Classifying Kiwifruits using Amazon Rekognition Custom Labels

Computer vision is a field of artificial intelligence (AI) that is gaining in popularity and interest largely due to increased access to affordable cloud-based training compute, more performant algorithms, and optimizations for scalable model deployment and inference. However, despite these advances in individual AI and machine learning (ML) domains, simplifying ML pipelines into coherent and […]

Batch image processing with Amazon Rekognition Custom Labels 

Amazon Rekognition is a computer vision service that makes it easy to add image and video analysis to your applications using proven, highly scalable, deep learning technology that requires no machine learning (ML) expertise to use. With Amazon Rekognition, you can identify objects, people, text, scenes, and activities in images and videos, as well as […]

The following diagram illustrates the serverless pipeline architecture.

Translate video captions and subtitles using Amazon Translate

September 2021: This post and the solution has been updated to use the Amazon EventBridge events notifications in Amazon Translate for tracking Amazon Translate Batch Translation job completion. Video is a highly effective a highly effective way to educate, entertain, and engage users. Your company might carry a large collection of videos that include captions […]

The following diagram illustrates this architecture covering the last three components.

Active learning workflow for Amazon Comprehend custom classification models – Part 2

Update Sep 2021: Amazon Comprehend has launched a suite of features for Comprehend Custom to enable continuous model improvements by giving developers the ability to version custom models, new training options for custom entity recognition models that reduce data preprocessing, ability to provide specific test sets during training, and live migration to new model endpoints. Refer to […]

Active learning workflow for Amazon Comprehend custom classification models – Part 1

Update Sep 2021: Amazon Comprehend has launched a suite of features for Comprehend Custom to enable continuous model improvements by giving developers the ability to version custom models, new training options for custom entity recognition models that reduce data preprocessing, ability to provide specific test sets during training, and live migration to new model endpoints. Refer to […]

From the following confusion matrix, we can see that the model does a better job at predicting for class 0 than class 1.

Utilizing XGBoost training reports to improve your models

In 2019, AWS unveiled Amazon SageMaker Debugger, a SageMaker capability that enables you to automatically detect a variety of issues that may arise while a model is being trained. SageMaker Debugger captures model state data at specified intervals during a training job. With this data, SageMaker Debugger can detect training issues or anomalies by leveraging […]

You already know how to use Amazon Athena to transform data in Amazon S3 using simple SQL commands

Translate, redact, and analyze text using SQL functions with Amazon Athena, Amazon Translate, and Amazon Comprehend

October 2021 Update (v0.3.0): Added support for Amazon Comprehend DetectKeyPhrases You have Amazon Simple Storage Service (Amazon S3) buckets full of files containing incoming customer chats, product reviews, and social media feeds, in many languages. Your task is to identify the products that people are talking about, determine if they’re expressing happy thoughts or sad […]