Deep Reinforcement Learning Humans excel at solving a wide variety of challenging problems, from low-level motor control through to high-level cognitive tasks. Deep Reinforcement learning (DRL) is an aspect of machine learning that leverages agents by taking actions in an environment to maximize the cumulative reward. DRL uses a paradigm of learning by trial-and-error, solely Read more...
Apache Spark is a very popular application platform for scalable, parallel computation that can be configured to run either in standalone form, using its own Cluster Manager, or within a Hadoop/YARN context. A growing interest now is in the combination of Spark with Kubernetes, the latter acting as a job scheduler and resource manager, and Read more...
This November, the VMware flagship conference VMworld Europe 2019 will again take place in Barcelona at the Fira Gran Via. The Virtualizing Business Critical Applications track this year is packed with a lot of sessions with a highlight being the Virtualizing Business Critical Applications customer tutorials (bootcamps) – four hours deep dive sessions (Level 400) Read more...
In part 1 of the blog we introduced end to end machine learning. The conceptual architecture with all software and hardware components for the solution was described. The steps in the solution deployment were shown. Sentiment Analysis basics Sentiment Analysis is a binary classification task. It predicts positive or negative sentiment using raw user text. Read more...
This article directs you to a recent webinar that VMware produced on the topic of executing distributed machine learning with TensorFlow and Horovod running on a set of VMs on multiple vSphere host servers. Many machine learning problems are tackled using a single host server today (with a collection of VMs on that host). However, Read more...
