How to develop a successful ML product? Part IV

25 March 2022

In today’s presentation by Omar Richardson, we discuss how to monitor performance and use MLOps to maintain prediction quality. It is important to remember that an ML project is not completed when your model is deployed. Instead of a fixed training set, your model is now exposed to real life data, posing its own challenges. Learn more…

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How to develop a successful ML product? Part III

26 February 2022

In the today’s presentation on “end-to-end” ML product development, we discuss on how to put model into production. After a data scientist made their model, there are two aspects to be considered: deployment infrastructure and code quality in model development. Want to learn more, check the presentation by Magnus Heskestad Waage.  …

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How to develop a successful ML product? Part II

17 February 2022

We continue our series of presentations on “end-to-end” ML product development. Today we discuss aspects related to understanding and processing of data in order to prepare it for the modeling phase. We’ve all been there: At the start of a project you’re given a data dump or access to a database. The task is now to…

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How to develop a successful ML product? Part I

13 February 2022

Do you know what does it take to develop a successful ML product? We start a series of presentations, we call “end-to-end ML development”, where we cover a 360-process in the design and making of ML/AI products. The goal of this series is to provide a high-level understanding of ingredients required for successful and efficient…

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Delighted to present the newest bright mind to join us: Anders Varmann Aamodt

09 February 2022

Anders has a background in physics from the University of Dundee and Imperial College London, where his academic track was lauded with numerous prizes for outstanding merit. His thesis focused on a novel computational strategy for the motion of charged particles and was passed with distinction. With expertise in scientific computing, embedded real-time software and performance…

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