Early this year IBM announced Deep Learning as a Service within Watson Studio. The core of this service is available as open source and can be run on Kubernetes clusters. This allows developers and...

Building machine and deep learning models from scratch is often not trivial, not for developers and sometimes not even for data scientists. Fortunately over the last years several models have been ...

Many developers, including myself, want to use AI in their applications. Building machine learning models however, often requires a lot of expertise and time. This article describes a technique cal...

While it has been possible to deploy TensorFlow models to mobile and embedded devices via TensorFlow for Mobile for some time, Google released an experimental version of TensorFlow Lite as an evolu...

In March IBM launched the Model Asset Exchange which is a place for developers to find and use open source deep learning models. In this article I describe how developers can use these models in ap...

In March IBM announced Deep Learning as a Service (DLaaS) which is part of IBM Watson Studio. Below I describe how to use this service to train models and how to optimize hyperparameters to easily ...

Recently Google introduced TensorFlow.js, which is a JavaScript library for training and deploying machine learning models in browsers and on Node.js. I like especially the ability to run predictio...

I’ve continued to play with Unity and the IBM Watson SDK, which allows using cognitive services like speech recognition in Unity projects. With this technology you can not only build games, but als...

Over the last days I’ve enjoyed playing with Unity and the IBM Watson SDK, which allows using cognitive services like speech recognition in Unity projects. With this technology you can not only bui...

Last week my colleagues and I attended We Are Developers in Vienna, a developer conference with 8000 attendees. We presented and demonstrated the IBM Cloud and the IBM Code developer site. Below ar...