PyData Meetup @ Vanderlande: ML Automation in the logistics domain

It is time for another edition of the PyData Eindhoven meetup. Join us on the 5th of September at Vanderlande for an evening of technical talks for technical people. We are organising this event around the theme: ML Automation in the logistics domain.

17:30 - Doors Open
18:00 - Welcome
18:05 - Welcome from Vanderlande
18:10 - Secure MLOps with MLFlow simplifying integration tests at NS by Luuk van der Velden (Codebeez)
18:40 - Dinner
19:15 - Practical use of MLOps tools for automated visual inspection by Thomas Woudsma (Prodrive Technologies)
19:45 - Collaborative picking guided by Deep Reinforcement Learning by Kasper Hendriks (Vanderlande) and Igor Smit (TU/e)
20:15 - Wrap/up20:20 - Networking Drinks
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Title: Secure MLOps with MLFlow simplifying integration tests at NS
Description: Cloud security teams want us to duplicate our resources across subscriptions and environments for security and privacy reasons. Data science applications struggle to be tested in the absence of real-world production data. At NS we performed integration tests on non-production data, but this broke down often and it was costly to maintain two separate data lakes (staging, production). Here I present our open source MLFlow client (Python) that allowed us to reduce the complexity of our test setup and reduce maintenance costs.
Presenter: Luuk van der Velden
**Company: https://codebeez.nl**
**LinkedIn: https://www.linkedin.com/in/ljjvandervelden/**
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Title: Practical use of MLOps tools for automated visual inspection
Description: Using deep learning to solve many real-world problems is becoming more and more ubiquitous. Especially for applications using image data, models created with TensorFlow or PyTorch achieve state-of-the-art performance. The next challenge is to keep these models at peak performance in production scenarios. Like with DevOps for software development, MLOps practices like data engineering, model engineering, and model serving and monitoring have been defined to streamline ML applications.

I this talk we will look at the application automated visual inspection in the electronics manufacturing facilities of Prodrive Technologies. Some of the latest model architectures are shown together with MLOps tools like MLflow (experiment tracking and model registration) and Seldon Core (model deployment and serving) including some examples in Python to give some technical insight into how these tools can be used.
Presenter: Thomas Woudsma
**Company: https://prodrive-technologies.com**
**LinkedIn: https://www.linkedin.com/in/thomaswoudsma/**
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Title: Collaborative picking guided by Deep Reinforcement Learning
Description: Collaborative case picking is Vanderlande's next step in improving picking efficiency in warehousing. This is achieved by leveraging the collaboration between human pickers and autonomous vehicles. However, the complexity and inherited uncertainty of warehouse operations make orchestrating this collaboration challenging for existing warehouse management software.
In this talk, we will look at how we can model collaborative case picking effectively using Python and showcase how this enables us to use DRL to improve over traditional optimization approaches.
Presenter: Kasper Hendriks and Igor Smit.
Company: Vanderlande
**LinkedIn: https://www.linkedin.com/in/kasper-hendriks/ & https://www.linkedin.com/in/igor-smit/**

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Attendee profile:
* People who want to learn about Python, Julia, R in the context of Data
* Interested in seeing how others use Python for solving real problems
* Interested in being part of the Python Community in Eindhoven
* No Recruiters
* No Sales
* Only people who speak Data