IBM is pushing it as a pipeline for building, managing, and running machine learning models through visual tools for each step of the process and RESTful APIs for deployment and management.

Niagara Bottling implemented the IBM Data Science Experience (DSX) platform and IBM Watson Studio to build data models using open-source tools such as Python. The goal was to study how to reduce ...

IBM claims its z Systems mainframe is capable of processing up to 2.5 billion transactions in a day. IBM Machine Learning for z/OS helps extract greater value from z Systems data without moving ...

They leverage machine learning models to make sense of content such as text, speech, images and videos. The IBM Watson Studio has better natural language processing tools that make it easier for ...

You can develop and test Python 2 and Python 3 language modules using Jupyter Notebooks, extended with the Azure Machine Learning Python client library (to work with your data stored in Azure ...

Today IBM announced IBM Machine Learning, the first cognitive platform for continuously creating, training and deploying a high volume of analytic models in the private cloud at the source of vast ...

IBM Corp. said today it’s hoping to provide a standardized solution for developers to create and deploy machine learning models in production and make them portable to any cloud platform. To do ...

The solution works with popular open source tools including languages like Scala, Java and Python, and machine learning frameworks like Apache SparkML, TensorFlow and H2O.

IBM’s Watson Studio is the company’s service for building machine learning workflows and training models, is getting a new addition today with the launch of Deep Learning as a Service (DLaaS).