Session Outline At LeoVegas, the nature of our campaigns and promotions poses interesting challenges for email optimization. The immense level of personalization available, from timing and frequency of send outs, to the...
Category - Nordic Data Science and Machine Learning Summit 2022
Building towards a mature machine learning lifecycle – MLOps at Swedbank – Varun Bhatnagar, Swedbank AB
Session Outline In the year 2022, the year of machine learning, you’re faced with two choices: a Blue pill that brings an end to the discussion, or a Red pill that propels you into an adventurous journey. This...
Building a scalable and centralized Analytics Platform for Norway’s largest bank – Trung-Duy Nguyen & Benjamin Tapley, DNB Bank ASA
Session Outline A walkthrough of how we are building our in-house Analytics Platform on the Cloud. We will discuss the normal daily workflows of data science users in our company and the development of our platform...
Building a Powerful User Behavior Analytics System Using Snowflake – Oskar Eriksson, Snowflake
Session Outline User behavior analytics (UBA), also known as user and entity behavior analytics (UEBA), is catching increasing attention in the IT & security community as a proven behavior based insider risk...
Infrastructure-agnostic Machine Learning Platform – Denys Kovalenko, Bolt
Session Outline At Bolt, we want scientists and engineers to solve customer’s problems, not infrastructure ones. That’s why we’ve been investing into centralized machine learning infrastructure for 3 years, and it...
Rise of the Data Products Platform – Iker Martinez de Apellaniz, Adevinta
Session Outline Since Data mesh started to get discussed, many companies have started to adopt it. In Adevinta, we have embraced the data products platform as the way to go, to ensure that Data products are being built...
Iterate on Data in Production – Safely – Micha Ben Achim Kunze, Maersk
Session Outline Production data is all you need. We will show how we build and iterate on data and ML products in our production environment. Using the established practice of feature flags in our setup we will try to...
Building a DS/ML capability that scales for Enterprises – Dael Williamson, Databricks
Session Outline Databricks have created, contributed toward, fostered the growth of, and donated some of the most impactful innovations in modern open source technology. Open data lakehouses are quickly becoming the...
ML Training in Production at Meta – Shivam Bharuka, Meta
Session Outline Machine learning models are growing rapidly in scale in order to support the recommendation and content understanding use-cases at Meta. In order to keep up with this growth, we have re-architected the...