It wasn't so long ago that developing custom artificial intelligence was very, very hard. Then came along several software libraries and frameworks, from PyTorch to Keras to MXNet to TensorFlow, that ...

Overview: AI in financial services uses machine learning and automation to analyze data in real time, improving speed, accuracy, and decision-making across bank ...

Seattle-based Kaskada claims to be the first company to train machines using event-based data and real-time data being fed from streaming sources. Database-as-a-service (DBaaS) provider DataStax on ...

Azure Machine Learning Service is Microsoft’s latest offering for developers and data scientists in the custom cloud machine learning and deep learning category. Azure Machine Learning Service adds to ...

Microsoft has expanded the data-analysis offerings on its Azure cloud, offering a machine learning service to help organizations derive more insight from mountains of unstructured data. The new ...

Amazon Monitron provides customers an end-to-end machine monitoring solution comprised of sensors, gateway, and machine learning service to detect abnormal equipment conditions that may require ...

At the Amazon Web Services re:Invent conference today, AWS CEO Andy Jassy introduced a fully managed, end-to-end machine learning service — SageMaker. The company says SageMaker will enable developers ...

LONDON--(BUSINESS WIRE)--Technavio has been monitoring the global machine learning-as-a-service (MLaaS) market since 2016 and the market is poised to grow by USD 8 billion during 2019-2023, ...

Unlock the full InfoQ experience by logging in! Stay updated with your favorite authors and topics, engage with content, and download exclusive resources. Vivek Yadav, an engineering manager from ...

Machine learning platforms are one of the fastest growing services of the public cloud. Unlike other cloud-based services, ML and AI platforms are available through diverse delivery models such as ...

Machine learning has experienced an incredible increase in usage in the past couple of years. In 2017, deploying machine learning models was considered extremely difficult, something only major ...