Blog

ML Conference
The Conference for Machine Learning Innovation
18. - 20. Juni 2018 | München

16
Nov

AI as a smart services for everyone

If you cannot or do not want to build an AI project from scratch, you have countless choices of ready-made services. But what can you do if the finished services do not fit the project? Customizable AI and ML models in the cloud, which you can train with your own data, provide a remedy.
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.
29
Oct

Coding deep learning: The absolute minimum an interested developer should know

Deep Learning is all the hype these days, beating another record most every week but writing code for deep learning is not just coding – it really helps if you have a basic understanding of what’s going on beneath. In this session from last year’s ML Conference, Sigrid Keydana offers a quick lesson on deep learning, as well as some tips and tricks for developers who’d like to dip their toes into this topic.
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.

Behind the Tracks