AWS Machine Learning Blog

Category: Artificial Intelligence

Reinventing retail with no-code machine learning: Sales forecasting using Amazon SageMaker Canvas

Retail businesses are data-driven—they analyze data to get insights about consumer behavior, understand shopping trends, make product recommendations, optimize websites, plan for inventory, and forecast sales. A common approach for sales forecasting is to use historical sales data to predict future demand. Forecasting future demand is critical for planning and impacts inventory, logistics, and even […]

Train machine learning models using Amazon Keyspaces as a data source

Many applications meant for industrial equipment maintenance, trade monitoring, fleet management, and route optimization are built using open-source Cassandra APIs and drivers to process data at high speeds and low latency. Managing Cassandra tables yourself can be time consuming and expensive. Amazon Keyspaces (for Apache Cassandra) lets you set up, secure, and scale Cassandra tables […]

Solution overview

Improve organizational diversity, equity, and inclusion initiatives with Amazon Polly

Organizational diversity, equity and inclusion (DEI) initiatives are at the forefront of companies across the globe. By constructing inclusive spaces with individuals from diverse backgrounds and experiences, businesses can better represent our mutual societal needs and deliver on objectives. In the article How Diversity Can Drive Innovation, Harvard Business Review states that companies that focus […]

Use Serverless Inference to reduce testing costs in your MLOps pipelines

Amazon SageMaker Serverless Inference is an inference option that enables you to easily deploy machine learning (ML) models for inference without having to configure or manage the underlying infrastructure. SageMaker Serverless Inference is ideal for applications with intermittent or unpredictable traffic. In this post, you’ll see how to use SageMaker Serverless Inference to reduce cost when […]

Accelerate and improve recommender system training and predictions using Amazon SageMaker Feature Store

August 30, 2023: Amazon Kinesis Data Analytics has been renamed to Amazon Managed Service for Apache Flink. Read the announcement in the AWS News Blog and learn more. Many companies must tackle the difficult use case of building a highly optimized recommender system. The challenge comes from processing large volumes of data to train and […]

Translate, redact and analyze streaming data using SQL functions with Amazon Kinesis Data Analytics, Amazon Translate, and Amazon Comprehend

August 30, 2023: Amazon Kinesis Data Analytics has been renamed to Amazon Managed Service for Apache Flink. Read the announcement in the AWS News Blog and learn more. You may have applications that generate streaming data that is full of records containing customer case notes, product reviews, and social media messages, in many languages. Your […]

Amazon SageMaker Notebook Instances now support configuring and restricting IMDS versions

Today, we’re excited to announce that Amazon SageMaker now supports the ability to configure Instance Metadata Service Version 2 (IMDSv2) for Notebook Instances, and for administrators to control the minimum version with which end-users create new Notebook Instances. You can now choose IMDSv2 only for your new and existing SageMaker Notebook Instances to take advantage […]

Reimagine search on GitHub repositories with the power of the Amazon Kendra GitHub connector

Amazon Kendra offers highly accurate semantic and natural language search powered by machine learning (ML). Many organizations use GitHub as a code hosting platform for version control and to redefine collaboration of open-source software projects. A GitHub account repository might include many content types, such as files, issues, issue comments, issue comment attachments, pull requests, […]

Merge cells and column headers in Amazon Textract tables

Financial documents such as bank, loan, or mortgage statements are often formatted to be visually appealing and easy to read for the human eye. These same features can also make automated processing challenging at times. For instance, in the following sample statement, merging rows or columns in a table helps reduce information redundancy, but it […]

Detect financial transaction fraud using a Graph Neural Network with Amazon SageMaker

Fraud plagues many online businesses and costs them billions of dollars each year. Financial fraud, counterfeit reviews, bot attacks, account takeovers, and spam are all examples of online fraud and malicious behaviors. Although many businesses take approaches to combat online fraud, these existing approaches can have severe limitations. First, many existing methods aren’t sophisticated or […]