Process Amazon Redshift data and schedule a training pipeline with Amazon SageMaker Processing and Amazon SageMaker Pipelines

Favorite Customers in many different domains tend to work with multiple sources for their data: object-based storage like Amazon Simple Storage Service (Amazon S3), relational databases like Amazon Relational Database Service (Amazon RDS), or data warehouses like Amazon Redshift. Machine learning (ML) practitioners are often driven to work with objects

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Shared by AWS Machine Learning December 16, 2021

Build GAN with PyTorch and Amazon SageMaker

Favorite GAN is a generative ML model that is widely used in advertising, games, entertainment, media, pharmaceuticals, and other industries. You can use it to create fictional characters and scenes, simulate facial aging, change image styles, produce chemical formulas synthetic data, and more. For example, the following images show the

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Shared by AWS Machine Learning December 16, 2021

Build a computer vision model using Amazon Rekognition Custom Labels and compare the results with a custom trained TensorFlow model

Favorite Building accurate computer vision models to detect objects in images requires deep knowledge of each step in the process—from labeling, processing, and preparing the training and validation data, to making the right model choice and tuning the model’s hyperparameters adequately to achieve the maximum accuracy. Fortunately, these complex steps

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Shared by AWS Machine Learning December 16, 2021

Incentivising Knowledge Management; lessons from NASA

Favorite Here is insight into how NASA tackles the issue of incentives and motivation for KM behaviours.   Image from wikimedia commons Incentives and motivation has long been a topic on this blog.  Here in Knoco we believe in intrinsic motivation rather than motivation through rewards or prizes, preferring to

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Shared by Nick Milton December 14, 2021

Live transcriptions of F1 races using Amazon Transcribe

Favorite The Formula 1 (F1) live steaming service, F1 TV, has live automated closed captions in three different languages: English, Spanish, and French. For the 2021 season, FORMULA 1 has achieved another technological breakthrough, building a fully automated workflow to create closed captions in three languages and broadcasting to 85

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Shared by AWS Machine Learning December 13, 2021

Hierarchical Forecasting using Amazon SageMaker

Favorite Time series forecasting is a common problem in machine learning (ML) and statistics. Some common day-to-day use cases of time series forecasting involve predicting product sales, item demand, component supply, service tickets, and all as a function of time. More often than not, time series data follows a hierarchical

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Shared by AWS Machine Learning December 13, 2021

Plan the locations of green car charging stations with an Amazon SageMaker built-in algorithm

Favorite While the fuel economy of new gasoline or diesel-powered vehicles improves every year, green vehicles are considered even more environmentally friendly because they’re powered by alternative fuel or electricity. Hybrid electric vehicles (HEVs), battery only electric vehicles (BEVs), fuel cell electric vehicles (FCEVs), hydrogen cars, and solar cars are

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Shared by AWS Machine Learning December 9, 2021