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.
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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.
Deep down ML is a pure numbers game. With very few exceptions, the actual input to an ML Model is always a collection of float values. We talked with Christoph Henkelmann about the way ML algorithms work on words and letters, the difference between image and text and how to handle textual input properly.