Tag: IT AI ML

In this post, we use Redshift ML to perform unsupervised learning on unlabeled training data using the K-means algorithm.

This article describes an architecture for many models that uses Machine Learning and compute clusters.

The AWS Well-Architected Framework provides you with a formal approach to compare your workloads against best practices. It also includes guidance on how to make improvements. Machine learning (ML) algorithms discover and learn patterns in data, and construct mathematical models to predict future data.

In software engineering, Continuous Integration (CI) and Continuous Delivery (CD) are two very important concepts. CI is when you integrate changes (new features, approved code commits, etc.) into your system reliably and continuously.

In this post, we show how to integrate the standard data preparation steps with training an ML model and running inference on a pre-trained model via DataBrew and AWS Step Functions. The solution is architected with an ML pipeline that trains the publicly available Air Quality Dataset to predict the CO levels in New York City.

Multi-modal transportation is one of the biggest developments in the logistics industry. There has been a successful collaboration across different transportation partners in supply chain freight forwarding for many decades. But there’s still a considerable overhead of paperwork processing for each leg of the trip.

As part of AWS Professional Services , we work with customers across different industries to understand their needs and supplement their teams with specialized skills and experience. Some of our customers are internal teams from the Amazon retail organization who request our help with their initiatives.

This post is co-written with Karim Prasla and Deepti Bhanti from Magellan Rx Management as the lead authors. Amazon Redshift ML makes it easy for data scientists, data analysts, and database developers to create, train, and use machine learning (ML) models using familiar SQL commands in Amazon Redshift data warehouses.

Today’s modern applications use multiple purpose-built database engines, including relational, key-value, document, and in-memory databases. This purpose-built approach improves the way applications use data by providing better performance and reducing cost.

The global retail market continues to grow larger and the influx of consumer data increases daily. The rise in volume, variety, and velocity of data poses challenges with demand forecasting and inventory planning. Outdated systems generate inaccurate demand forecasts.

Amazon Athena is an interactive query service that makes it easy to analyze data in a data lake using standard SQL. One of the key elements of Athena is that you only pay for the queries you run. This is an attractive feature because there is no hardware to set up, manage, or maintain.

This post is co-written with Clay Martin and Ajay Joshi from Jobcase as the lead authors. Jobcase is an online community dedicated to empowering and advocating for the world’s workers. We’re the third-largest destination for job search in the United States, and connect millions of Jobcasers to relevant job opportunities, companies, and other resources on a daily basis.

This post is co-authored with Piotr Klesta, Robert Meisner and Lukasz Luszczynski of ERGO Artificial intelligence (AI) and related technologies are already finding applications in our homes, cars, industries, and offices. The insurance business is no exception to this.

In this post, we cover some of the most common query patterns to run on streaming data using Apache Flink relational APIs. Out of the two relational API types supported by Apache Flink, SQL and Table APIs, our focus is on SQL APIs. We expect readers to have knowledge of Kinesis Data Streams, AWS Glue, and AWS Identity and Access Management (IAM). In this post, we use a sales transaction use case to walk you through the examples of tumbling, sliding, session and windows, group by, and joins query operations. We expect readers to have a basic knowledge of SQL queries and streaming window concepts.