This August, the VMware flagship conference VMworld 2019 will again take place in San Francisco at the Moscone Center. A highlight of the event this year will be the Virtualizing Applications customer workshops. This is the 4th consecutive year that this elite program has been offered as an extended learning opportunity for Read more...
In this article, we explore the tools and process for (1) training a machine learning model on a given dataset using the H2O Driverless AI (DAI) tool, and (2) deploying a trained model, as part of a scoring pipeline, to a REST server for use by business applications. All of the infrastructure requirements for this Read more...
In part 1 we introduced the solution and its deployment. In part 2 we will look at the validation of the solution and the results. Testing Methodology: The goal of the testing is to validate the vSphere platform for running Caffe2 and PyTorch. Some of the capabilities such as sharing GPUs between containers was Read more...
Introduction Kubernetes is a popular platform to deploy modern applications. In an earlier blog we look at how Tensorflow can be leveraged in the vSphere platform for common ML use cases. In this series we will look at running Caffe2 and PyTorch which are popular open source ML platforms. This solution focused on validating Caffe2 Read more...
In an earlier VMware blog article and demo on machine learning, we used the H2O Driverless AI tool, deployed on VMware vSphere-based VMs, for feature engineering, choosing and training a machine learning model and finally for creation of a deployable ML pipeline. A big advantage of using this H2O Driverless AI tool in virtual machine form on Read more...
