Thu Apr 13 2023

Data & Drinks meets Amsterdam Applied Machine Learning (Spotify & Databricks)

Raamstraat 7, Amsterdam - HQ Xomnia


Join us for a special edition of our monthly event, which we are proud to co-host with Gijs Molenaar's Meetup, Amsterdam Applied Machine Learning. Join us on April 13th at Xomnia's HQ in Amsterdam to attend two interesting talks presented by guest speakers from two world-renowned brands: Spotify & Databricks.

Our first talk is presented by Staff Machine Learning Engineer at Spotify Brammert Ottens, who will talk about what makes Spotify's search engine unique. Our second talk is presented by Sr. Strategic Architect Ivo Everts and Staff Delivery Solution Architect Anestis Pontikakis from Databricks. They will deliver a talk titled "Happy Sensor Data for Good Models and Collaboration".

The event includes dinner, drinks and a lot of networking opportunities with data professionals from Amsterdam and beyond.

Summary of talks:
Talk #1: What makes Spotify Search tick? by Brammert Ottens:
In this talk, Brammert will talk about what makes Spotify's search unique, the kinds of challenges that they have and how they have solved some of them. Challenges include, for instance, having a single search system to deal with many different types of content, from tracks to podcast shows, each of which comes with different features and representations. Another challenge is how Spotify deals with instant search and the many prefix searches that come with that.

Talk #2: Happy Sensor Data for Good Models and Collaboration by Ivo Everts and Anestis Pontikakis:
Our speakers will present the Real Time Data Ingestion Platform SDK, which has been published at Linux Foundation Energy to collect vast amounts of sensor measurements needed for the modelling and simulations of assets in the Digital Twin. The SDK is based on open source Databricks technology and is developed at Shell, with the goal to accelerate the energy transition through open source and data sharing.

About the speakers:

  • Brammert Ottens: Brammer is a staff machine learning engineer at Spotify. He holds an MSc in AI and Logic from the University of Amsterdam, and a PhD in AI from EPFL. He worked on scheduling and planning problems for Quintiq, and customer service optimization, search and MLOps for For the last three years, he has been working on Spotify Search.
  • Ivo Everts: With over 20 years of academic and industrial experience in AI, Ivo's passion for value creation from data always thrives. Having moved from science to consultancy and from pre-sales to strategy at Databricks, he helps large organizations to be successful with data and AI.
  • Anestis Pontikakis: With 20+ years of broad industry experience in technology, Anestis joined Databricks in 2020 and as a deep generalist has helped Shell with over 100 use cases to date. As a delivery solution architect, Anestis connects and brings together the business and technical elements of data projects, looking after long-term customer success by understanding the numerous businesses of Shell and supporting the teams in technical decisions.