Category - Nordic Data Science and Machine Learning Summit 2018

AWS has democratized ML and Deep Learning for the masses. Principles to maintain, scale and deploy Machine Learning and Deep Learning. Key Takeaways Challenges from going from idea, model, deployment, to life cycle...

Briefly describing some scalability challenges facing machine learning in big and small companies. Introducing content/data lake architectures and their impact on scalability. Presenting principals for building lakes...

We had a data warehouse and a data lake that were very disparate. How do we take that noise and transform it into something useful? Pentaho was the glue that made our data scientists more efficient Key Takeaways ZeniMax...

The game industry is experiencing a paradigm shift that sees games as services. This shift entails a different way to understand player behavior: the communities of players become fundamental elements for a game’s...

The presentation will walk through Nordea’s journey in creating our Virtual Assistant Platform. Key Takeaways Value proposition of a virtual assistant in banking environment Machine learning and AI aspects of...

Klarna has a strong focus on making complicated things simple for end users. In this talk, we share how we use a variety of machine learning techniques to create functionality that enables us to automate web...

This session focuses on how typical business problems in e-commerce are solved at LeoVegas. We explore how applying artificial intelligence yields powerful solutions to customer acquisition, customer interactions as...

This session will describe an end-to-end data science project accomplished by a small team (4 members) at a small company (16 employees), that achieved a great result: the International Smart Grid Action Network’s...