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 ...

A new algorithm is enabling deep learning that is more collaborative and communication-efficient than traditional methods. Army researchers developed algorithms that facilitate distributed ...

We wondered what Rocklin's view on this is, and what he sees as the greatest challenges and opportunities for distributed machine learning going forward. Also: For CockroachDB, transactions ...

But in order to obtain effective data and results, it’s important that you have a basic understanding of how it works with machine learning. In this introductory tutorial, you’ll learn the basics of ...

Existing Caffe models can be upgraded to Caffe2 with a script. By abstracting away the complexity of distributed machine learning, H2O makes it easy for organizations to build data models and ...