AWS Machine Learning Blog

Category: Artificial Intelligence

This dataset contains 500 images of bees that have been uploaded by iNaturalist users for the purposes of recording the observation and identification.

Training and deploying models using TensorFlow 2 with the Object Detection API on Amazon SageMaker

With the rapid growth of object detection techniques, several frameworks with packaged pre-trained models have been developed to provide users easy access to transfer learning. For example, GluonCV, Detectron2, and the TensorFlow Object Detection API are three popular computer vision frameworks with pre-trained models. In this post, we use Amazon SageMaker to build, train, and […]

Greg Baker at his work station.

Learn from the winner of the AWS DeepComposer Chartbusters Track or Treat challenge

AWS is excited to announce the winner of the AWS DeepComposer Chartbusters Track or Treat challenge, Greg Baker. AWS DeepComposer gives developers a creative way to get started with machine learning (ML). In June 2020, we launched Chartbusters, a global competition in which developers use AWS DeepComposer to create original AI-generated compositions and compete to […]

Amazon DevOps Guru is powered by pre-trained ML models that encode operational excellence

On December 1, 2020, we announced the preview of Amazon DevOps Guru, a machine learning (ML)-powered service that gives operators of cloud-based applications a simpler way to measure and improve an application’s operational performance and availability to reduce expensive downtime. Amazon DevOps Guru is a turn-key solution that helps operators by automatically ingesting operational data […]

Anomaly detection with Amazon Lookout for Metrics

This is a guest blog post from Quantiphi, an AWS Advanced Consulting Partner that specializes in artificial intelligence, machine learning, and data and analytics solutions. We’ve all heard the saying “time is money,” and that’s especially true for the retail industry. In a highly competitive environment where large volumes of data are generated, quick and […]

The following diagram illustrates the overall architecture of this approach.

Using genetic algorithms on AWS for optimization problems

Machine learning (ML)-based solutions are capable of solving complex problems, from voice recognition to finding and identifying faces in video clips or photographs. Usually, these solutions use large amounts of training data, which results in a model that processes input data and produces numeric output that can be interpreted as a word, face, or classification […]

Creating a BankingBot on Amazon Lex V2 Console with support for English and Spanish

Creating a BankingBot on Amazon Lex V2 Console with support for English and Spanish

This blog post was last reviewed and updated August, 2022 with updated verbiage and screenshots for BankingBot. Amazon Lex is a service for building conversational interfaces into any application. The new Amazon Lex V2 Console and APIs make it easier to build, deploy, and manage bots. In this post, you will learn about about the […]

The following diagram illustrates our architecture.

Using Amazon Translate to provide language support to Amazon Kendra

Amazon Kendra is a highly accurate and easy-to-use intelligent search service powered by machine learning (ML). Amazon Kendra supports English. This post provides a set of techniques to provide non-English language support when using Amazon Kendra. We demonstrate these techniques within the context of a question-answer chatbot use case (Q&A bot) where a user can […]

Using the AWS DeepRacer new Soft Actor Critic algorithm with continuous action spaces

AWS DeepRacer is the fastest way to get started with machine learning (ML). You can train reinforcement learning (RL) models by using a 1/18th scale autonomous vehicle in a cloud-based virtual simulator and compete for prizes and glory in the global AWS DeepRacer League. We’re excited to bring you two new features available on the […]

Scheduling work meetings in Slack with Amazon Lex

Imagine being able to schedule a meeting or get notified about updates in your code repositories without leaving your preferred messaging platform. This could save you time and increase productivity. With the advent of chatbots, these mundane tasks are now easier than ever. Amazon Lex, a service for building chatbots, offers native integration with popular […]

Automating complex deep learning model training using Amazon SageMaker Debugger and AWS Step Functions

Amazon SageMaker Debugger can monitor ML model parameters, metrics, and computation resources as the model optimization is in progress. You can use it to identify issues during training, gain insights, and take actions like stopping the training or sending notifications through built-in or custom actions. Debugger is particularly useful in training challenging deep learning model […]