AWS Machine Learning Blog

Category: Artificial Intelligence

Automate annotation of image training data with Amazon Rekognition

Every machine learning (ML) model demands data to train it. If your model isn’t predicting Titanic survival or iris species, then acquiring a dataset might be one of the most time-consuming parts of your model-building process—second only to data cleaning. What data cleaning looks like varies from dataset to dataset. For example, the following is […]

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Simplify patient care with a custom voice assistant using Amazon Lex V2

For the past few decades, physician burnout has been a challenge in the healthcare industry. Although patient interaction and diagnosis are critical aspects of a physician’s job, administrative tasks are equally taxing and time-consuming. Physicians and clinicians must keep a detailed medical record for each patient. That record is stored in the hospital electronic health […]

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TC Energy builds an intelligent document processing workflow to process over 20 million images with Amazon AI

This is a guest post authored by Paul Ngo, US Gas Technical and Operational Services Data Team Lead at TC Energy. TC Energy operates a network of pipelines, including 57,900 miles of natural gas and 3,000 miles of oil and liquid pipelines, throughout North America. TC Energy enables a stable network of natural gas and […]

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Simplify data annotation and model training tasks with Amazon Rekognition Custom Labels

For a supervised machine learning (ML) problem, labels are values expected to be learned and predicted by a model. To obtain accurate labels, ML practitioners can either record them in real time or conduct offline data annotation, which are activities that assign labels to the dataset based on human intelligence. However, manual dataset annotation can […]

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Smart city traffic anomaly detection using Amazon Lookout for Metrics and Amazon Kinesis Data Analytics Studio

Cities across the world are transforming their public services infrastructure with the mission of enhancing the quality of life of its residents. Roads and traffic management systems are part of the central nervous system of every city. They need intelligent monitoring and automation in order to prevent substantial productivity loss and in extreme cases life-threatening […]

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Use Amazon SageMaker Feature Store in a Java environment

Feature engineering is a process of applying transformations on raw data that a machine learning (ML) model can use. As an organization scales, this process is typically repeated by multiple teams that use the same features for different ML solutions. Because of this, organizations are forced to develop their own feature management system. Additionally, you […]

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Prepare and clean your data for Amazon Forecast

You might use traditional methods to forecast future business outcomes, but these traditional methods are often not flexible enough to account for varying factors, such as weather or promotions, outside of the traditional time series data considered. With the advancement of machine learning (ML) and the elasticity that the AWS Cloud brings, you can now […]

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Use contextual information and third party data to improve your recommendations

Have you noticed that your shopping preferences are influenced by the weather? For example, on hot days would you rather drink a lemonade vs. a hot coffee? Customers from consumer-packaged goods (CPG) and retail industries wanted to better understand how weather conditions like temperature and rain can be used to provide better purchase suggestions to […]

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Automate continuous model improvement with Amazon Rekognition Custom Labels and Amazon A2I: Part 2

In Part 1 of this series, we walk through a continuous model improvement machine learning (ML) workflow with Amazon Rekognition Custom Labels and Amazon Augmented AI (Amazon A2I). We explained how we use AWS Step Functions to orchestrate model training and deployment, and custom label detection backed by a human labeling private workforce. We described […]

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Automate continuous model improvement with Amazon Rekognition Custom Labels and Amazon A2I: Part 1

If you need to integrate image analysis into your business process to detect objects or scenes unique to your business domain, you need to build your own custom machine learning (ML) model. Building a custom model requires advanced ML expertise and can be a technical challenge if you have limited ML knowledge. Because model performance […]

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