Exposing the inferencing engine as an API makes it possible ... source platform for managing the machine learning lifecycle. “It can be a TensorFlow model or a scikit model,” Wiley said.

The result is a machine learning framework that is easier to work with—for example, by using the relatively simple Keras API for model training—and more performant. Distributed training is ...

Microsoft updated its machine learning dev tooling with ML.NET 2.0 and ... specifically one that enables a new text classification scenario in Model Builder, along with a sentence similarity API. The ...

Microsoft has released the 0.6 version of its ML.Net machine learning framework, aimed at .Net developers. The update adds a new and more useful model-building API set, the ability to use more ...

Search Engine Land » Platforms » Google » Google Ads » Machine Learning With AdWords ... actually build our model. To do this, we need to enable the Prediction API for our script under the ...

“The new machine learning models that power ... giving them the best possible ability to detect and model what should and shouldn’t be happening for API traffic. It is especially adept at ...

Offered as an AIaaS model, the APIs can perform various tasks ranging from summarization and content moderation to topic detection. “Our API platform ... Systems as a machine learning engineer ...

Currently, there are multiple companies that sell software packages that do just this—allow groups or individuals to create an artificial intelligence or machine learning model without needing ...

At the time, Google's neural network API supported on-device model creation ... come in handy for developers building on-device machine learning systems. The added acceleration via Qualcomm's ...

It allows apps to use machine learning for text recognition, face detection, scanning barcodes, and even detecting landmarks (similar to Google Lens). The new API uses Firebase, and is available ...