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.
PyTorch is currently one of the most popular frameworks for the development and training of neural networks. It is characterized above all by its high flexibility and the ability to use standard Python debuggers. And you don’t have to compromise on the training performance.
The cold start problem affects both startups as well as established companies. Nonetheless, it also provides a great opportunity to collect new data with your customer’s problem in focus. How do you solve the cold start problem and arrive at a useful data pipeline? We talked to ML Conference speakers Markus Nutz and Thomas Pawlitzki about all this and more.
Machine learning may have all sorts of use cases, but forecasting? In honor of the upcoming ML Conference, we talked to Philipp Beer about how data scientists can utilize ML in statistical forecasting. We talk about the advantages and disadvantages of modern vs. classical methods, how can one decide between the two, and where should they turn when they need good predictions for their business KPIs.
Machine learning enables customized conversations between man and machine that can result in buying decisions. We asked Tina Nord and Kathleen Jaedtke to explain how this can be achieved through the use of dialogue-oriented technologies. Let’s take a look at how communication between man and machines works.
We spoke to data expert Canburak Tümer about how machine learning is being used to detect fraud in sales transactions. Find out how ML technology is helping to keep this tricky job under control and what it looks for when crunching the data.
ML Conference-Speaker Christoph Henkelmann says machine learning is basically nothing more than a numbers game. We’ve taken a closer look at what he means by that and and asked him to explain the principles of word processing from the point of view of a machine in more detail.
Humanity is confronted more than ever with artificial intelligence (AI), yet it is still challenging to find a common ground. We talked with Marisa Tschopp, researcher at scip ag about Artificial Intelligent Quotient (A-IQ), how to automate A-IQ testing and more.
The countdown to the Machine Learning conference in Berlin keeps ticking. We spoke with ML conference speaker and ML6 head of Applied Research Xander Steenbrugge about the “black box problem” in neural networks. Catch more of AI expert Xander Steenbrugge during his keynote talk, session, and workshop.