We recently announced Amazon SageMaker Pipelines, the first purpose-built, easy-to-use continuous integration and continuous delivery (CI/CD) service for machine learning (ML). SageMaker Pipelines is a native workflow orchestration tool for building ML pipelines that take advantage of direct Amazon SageMaker integration. Three components improve the operational resilience and reproducibility of
Machine learning (ML)-based recommender systems aren’t a new concept across organizations such as retail, media and entertainment, and education, but developing such a system can be a resource-intensive task—from data labelling, training and inference, to scaling. You also need to apply continuous integration, continuous deployment, and continuous training to your
Your knowledge store should support people who browse as well as people who search. It should be like a shopper-friendly supermarket. Image from wikimedia commons Some shoppers know exactly what they want. They walk into the relevant store, ask an assistant where to find the item, and buy it. Others
A gym is a toolkit for developing and comparing reinforcement learning algorithms. Procgen Benchmark is a suite of 16 procedurally-generated gym environments designed to benchmark both sample efficiency and generalization in reinforcement learning. These environments are associated with the paper Leveraging Procedural Generation to Benchmark Reinforcement Learning (citation). Compared to
Machine learning (ML) is used throughout the financial services industry to perform a wide variety of tasks, such as fraud detection, market surveillance, portfolio optimization, loan solvency prediction, direct marketing, and many others. This breadth of use cases has created a need for lines of business to quickly generate high-quality
According to the International Chamber of Shipping, 90% of world commerce happens at sea. Vessels are transporting every possible kind of commodity, including raw materials and semi-finished and finished goods, making ocean transportation a key component of the global supply chain. Manufacturers, retailers, and the end consumer are reliant on
Amazon SageMaker Studio notebooks provide a full-featured integrated development environment (IDE) for flexible machine learning (ML) experimentation and development. Security measures secure and support a versatile and collaborative environment. In some cases, such as to protect sensitive data or meet regulatory requirements, security protocols require that public internet access be
We’re excited to announce the global availability of AWS Contact Center Intelligence (AWS CCI) solutions powered by AWS AI Services and made available through the AWS Partner Network. AWS CCI solutions enable you to leverage AWS machine learning (ML) capabilities with your current contact center provider to gain greater efficiencies
When you’ve got your hands full, so you use your voice to ask your phone to play your favorite song, it can feel like magic. In reality, it’s a more complicated combination of engineering, design and natural language processing at work, making it easier for many of us to use
A fresh new year is here, and we wish you all a wonderful 2021. We signed off last year at AWS re:Invent on the artificial intelligence (AI) and machine learning (ML) track with the first ever machine learning keynote and over 50 AI/ML focused technical sessions covering industries, use cases,
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Shared by AWS Machine Learning January 19, 2021
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