This project contains examples which demonstrate how to deploy analytic models to mission-critical, scalable production environments leveraging Apache Kafka and its Streams API. Models are built with ...

TensorFlow 2.0, released in October 2019, revamped the framework significantly based on user feedback. The result is a machine learning framework that is easier to work with—for example, by ...

The XGBoost machine learning algorithm was used to build an infection prediction model for NDMM patients with easy operation and good performance with an AUC of 0.884. This model can help determine ...

Then we're training our model (machine learning algorithm parameters) to map the input to the output correctly (to do correct prediction). The ultimate purpose is to find such model parameters that ...

Machine-learning prediction model for acute skin toxicity after breast radiation therapy using spectrophotometry Savino Cilla 1* Carmela Romano 1 Gabriella Macchia 2 Mariangela Boccardi 2 Donato ...

The model in the machine learning tool would then use an analytics tool called predictive analytics to make predictions on whether the mining industry will be profitable for a time period, or ...

Computer scientists at MIT joined forces with oceanographers to develop a machine-learning model that incorporates knowledge from fluid dynamics to generate more accurate predictions about the ...

AI will help over 50 percent of enterprise application workflows to better use legacy data, real-time operational data, and third-party data feeds Businesses will use 50 percent more automation ...