Honey bee colony assessment is usually carried out by manually counting and classifying comb cells. Thiago da Silva Alves explains in this interview how deep learning can help to accomplish this time-consuming and error-prone task.
Generative Adversarial Networks (GANs) have recently sparked an increasing amount of interest, as they can generate images of faces that look convincingly real. What else are they capable of, what risks could they pose in the long run, and what do they have in common with the emerging internet in the 1990’s? We interviewed ML Conference speaker Xander Steenbrugge.
.NET Core is not only including WPF and WinForms in the new open source implementation of .NET - Microsoft now wants to make machine learning usable for everyone. That's why machine learning is now making its way into .NET Core with the ML.NET Framework. In this series of articles, we'll show you what ML.NET can do, what options the developer has available, what the tooling and APIs look like, and what’s happening behind the scenes.
Machine Learning (ML) allows applications to obtain hidden knowledge without the need to explicitly program what needs to be considered in the process of knowledge discovery. This way, unstructured data can be analyzed, image and speech recognition can be improved and well-informed decisions can be made. In this article we will in particular discuss new trends and innovations surrounding Apache Kafka and Machine Learning.
You can't see the forest for the trees anymore, and you need new inspirations urgently? Then ML Conference is the place to be. Connect with like-minded people, widen your horizon while gaining deep insights and practical knowledge of the latest trends and technologies.
Can UX demystify AI? Ward Van Laer answers this question in his session at the ML Conference 2019. We invited him for an interview and asked him how to solve the black box problem in machine learning by merely improving the user experience.
In the field of machine learning, many ethical questions are taking on new meaning: On what basis does artificial intelligence make decisions? How can we avoid the transfer of social prejudices to machine learning models? What responsibility do developers have for the results of their algorithms? In his keynote from the Machine Learning Conference 2019, Eric Reiss examines dark patterns in the ethics of machine learning and looks for a better answer than "My company won’t let me do that."
Machine learning can be implemented in different ways, one of which is reinforcement learning. What exactly is reinforcement learning and how can we put it to use? Before the upcoming ML Conference, we spoke to Dr. Christian Hidber about the underlying ideas and challenges of reinforcement learning, and why it can be suited for application in an industrial setting.