AWS Machine Learning Blog

Category: Artificial Intelligence

The tech behind the Bundesliga Match Facts xGoals: How machine learning is driving data-driven insights in soccer

It’s quite common to be watching a soccer match and, when seeing a player score a goal, surmise how difficult scoring that goal was. Your opinions may be further confirmed if you’re watching the match on television and hear the broadcaster exclaim how hard it was for that shot to find the back of the […]

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Developing NER models with Amazon SageMaker Ground Truth and Amazon Comprehend

Named entity recognition (NER) involves sifting through text data to locate noun phrases called named entities and categorizing each with a label, such as person, organization, or brand. For example, in the statement “I recently subscribed to Amazon Prime,” Amazon Prime is the named entity and can be categorized as a brand. Building an accurate […]

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Generating compositions in the style of Bach using the AR-CNN algorithm in AWS DeepComposer

AWS DeepComposer gives you a creative way to get started with machine learning (ML) and generative AI techniques. AWS DeepComposer recently launched a new generative AI algorithm called autoregressive convolutional neural network (AR-CNN), which allows you to generate music in the style of Bach. In this blog post, we show a few examples of how […]

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Building a speech-to-text notification system in different languages with AWS Transcribe and an IoT device

Have you ever wished that people visiting your home could leave you a message if you’re not there? What if that solution could support your native language? Here is a straightforward and cost-effective solution that you can build yourself, and you only pay for what you use. This post demonstrates how to build a notification […]

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Building AI-powered forecasting automation with Amazon Forecast by applying MLOps

This post demonstrates how to create a serverless Machine Learning Operations (MLOps) pipeline to develop and visualize a forecasting model built with Amazon Forecast. Because Machine Learning (ML) workloads need to scale, it’s important to break down the silos among different stakeholders to capture business value. The MLOps model makes sure that the data science, […]

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Enhancing enterprise search with Amazon Kendra

Amazon Kendra is an easy-to-use enterprise search service that allows you to add search capabilities to your applications so end-users can easily find information stored in different data sources within your company. This could include invoices, business documents, technical manuals, sales reports, corporate glossaries, internal websites, and more. You can harvest this information from storage […]

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Scheduling Jupyter notebooks on SageMaker ephemeral instances

It’s 5 PM on a Friday. You’ve spent all afternoon coding out a complex, sophisticated feature engineering strategy. It just started working on your Amazon SageMaker Studio t3.medium notebook, and all you want to do is plug this onto a massive instance, scale it out over the rest of your dataset, and go home. You […]

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AWS DeepComposer Chartbusters: generate compositions in the style of Bach and compete to top the charts

We are excited to announce the launch of AWS DeepComposer Chartbusters, a monthly challenge where developers can use AWS DeepComposer to create original compositions and compete to top the charts and win prizes. AWS DeepComposer gives developers a creative way to get started with machine learning (ML) and generative AI techniques. With AWS DeepComposer, developers, […]

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Detecting fraud in heterogeneous networks using Amazon SageMaker and Deep Graph Library

Fraudulent users and malicious accounts can result in billions of dollars in lost revenue annually for businesses. Although many businesses use rule-based filters to prevent malicious activity in their systems, these filters are often brittle and may not capture the full range of malicious behavior. However, some solutions, such as graph techniques, are especially suited […]

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Integrate Amazon Kendra and Amazon Lex using a search intent

Customer service conversations typically revolve around one or more topics and contain related questions. Answering these questions seamlessly is essential for a good conversational experience. For example, as part of a car rental reservation, you have queries such as, “What’s the charge for an additional driver?” or, “Do you have car seats for kids?” Starting […]

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