Once training is done, the models can be easily exported to run on industry standard platforms and work in apps, websites or devices. That allows people to create end-to-end machine learning solutions ...

Source code for the tutorial 'Deploying a machine learning model with a Flask API' written for HyperionDev. In this tutorial we take the image classification model built in model.py which recognises ...

Official Python client for the MonkeyLearn API. Build and run machine learning models for language processing from your Python apps. MonkeyLearnException Base class ...

The relevant quantum properties allow developers to create ... complex machine learning problems. Still, QML has the potential to revolutionize classical machine learning by training models ...

Microsoft updated its machine ... learning models in those apps. Heading the highlights of ML.NET 2.0 are new APIs for working with text, specifically one that enables a new text classification ...

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 ...

Jobs interview platform Sapia.ai is opening up its machine learning models as part of a strategic API program, launching on AWS Marketplace ... “Companies that want to use our existing AI services to ...

“The new machine learning models that power our Apigee API abuse detection have been trained and used by Google’s internal teams to protect some of the company’s public-facing APIs ...

Businesses and developers will be able to build on the system to create custom chatbots and much more. The search giant is launching an API for ... and deploy machine learning models.

The implementation was used to create a dataset that continues ... and evaluation of a robust machine-learning model. The paper provides a thorough description of the implemented system architecture, ...