A common challenge for teams working on video machine learning applications   is how to scale and automate their ML lifecycle when working with these types of  large unstructured datasets. 

In this webinar Vincent Koops, Senior Data Scientist at RTL Netherlands, will walk through their Video AI platform at RTL and how they’ve addressed these challenges. Their platform is built on top of Pachyderm and Kubernetes to enable a wide range of ML applications such as automatic thumbnail picking and mid-roll marking.

Attendees will learn: 

  • How to take a modular approach to creating a scalable and automated ML platform
  • The challenges and best practices when working with unstructured data like video clips
  • Considerations your teams need to make to prevent human error while getting the most out of AI and ML

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Instructor's Bio

Vincent Koops
 Senior Data Scientist at RTL Netherlands

Hendrik Vincent Koops is an AI researcher and composer, holding degrees in Sound Design and Music Composition from the HKU University of the Arts Utrecht, and degrees in Artificial Intelligence from the Utrecht University. After a research internship at Carnegie Mellon University, he completed his PhD in Music Information Retrieval at Utrecht University. Currently, he is a Senior Data Scientist at RTL Netherlands working on AI Multimedia projects. He is responsible for developing a scalable video intelligence platform to make video content more discoverable, searchable and valuable. He develops AI solutions to automatically analyse music in video content, automatically generate movie trailers for different devices, and methods to automatically pick thumbnails for video content for the VOD-platform Videoland. Vincent is also a coorganizer of the international AI Song Contest, in which teams compete to write a song with AI.


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    ON-DEMAND WEBINAR: AI vs Unstructured Data: Best Practices for Scaling Video AI

    • Ai+ Training

    • Webinar recording