Blog

ML Conference
The Conference for Machine Learning Innovation
17 - 19 June 2019 | Munich

12
Nov

Too many ideas, too little data – Overcome the cold start problem

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.
9
Nov

“Designing proper data collection today improves the quality of ML outcomes tomorrow”

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.
15
May

Preparing Text Input for Machine Learning

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.
20
Apr

Cracking open the black box of Neural Networks

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.
9
Nov

Machine Learning as a microservice in a Docker container on a Kubernetes cluster — say what?

It is always fascinating to see the versatile ways in which machine learning can be used. At Outfittery, algorithms help the experts select the most suitable outfits for customers — quite literally. In this interview ML Conference speaker Jesper Richter-Reichhelm, CTO at Outfittery GmbH, explains how the company uses machine learning and which frameworks they use. He also tells us who makes better suggestions — human beings or machines.
29
Oct

“There are always surprises when you work with data because data is not very clean, naturally”

Our first ML Conference will debut in December in Berlin. Until then, we’d like to give you a taste of what’s to come. We talked with, Markus Ehrenmüller-Jensen, Business Intelligence Architect at Runtastic about how the company involves machine learning into their daily business, the benefits, the battle scars and everything in between. Also, you’ll get a sneak peek at his talk.

Behind the Tracks