Machine learning programming is an in-demand skill. Learn how to program an ML application with Python in this tutorial.

Analyzing Small-to-Medium Datasets When it comes time to develop a codified machine learning pipeline, for datasets that can be handled by a single node, it is hard to beat the Python-based ...

The future of machine learning is distributed If you are familiar with ML model deployment, you may know about PMML and PFA. PMML and PFA are existing standards for packaging ML models for deployment.

Once the training data is prepared, a distributed MPI application is then used to adjust the parameters of the machine- or deep-learning model through a ‘training’ or optimization procedure. All ...

Over the last couple of decades, those looking for a cluster management platform faced no shortage of choices. However, large-scale clusters are being asked to operate in different ways, namely by ...

Hot on the heels of Google releasing an open source machine learning framework, Microsoft has released a similar project called DMLT (Distributed Machine Learning Toolkit).

Japanese heavyweight NTT has come up with a way to carry out coordinated machine learning on multiple edge servers. It is similar to a blockchain or an artificial neural network, in that it is ...

TensorFlow 0.8 adds distributed computing support to speed up the learning process for Google's machine learning system. Written by Larry Dignan, Contributor April 13, 2016 at 10:00 a.m. PT ...