OpenRewrite & Machine Learning 101

⚠ Due to the original venue closing early, we have switched locations. The new adress is: Helperpark 258-L, Groningen.

At this second event we have two talks for you: Write your custom OpenRewrite recipes by Tim te Beek & Machine Learning 101: Where to begin? by Lutske de Leeuw. Both talks will be in English.

The venue opens at 16:30, the first talk will start at 17:00. In between the sessions there will be drinks and dinner.

Signing up and valid identification are mandatory as these are required to enter the building. If your name on meetup does not match your identification, please contact Martijn (organiser) with your full name.

Write your custom OpenRewrite recipes - Tim te Beek (Moderne)
OpenRewrite allows you to automate the maintenance on your code. A large collection of existing recipes allows you to upgrade, improve and secure your applications. But what if you want something beyond what’s already available out of the box?
In this live demo we’ll explore writing custom OpenRewrite recipes. That might be small additions to existing migration recipes, or larger efforts to adopt breaking changes. Walk away knowing exactly how to upgrade that internal library or framework, or how to contribute recipes that everyone can then use.

Machine Learning 101: Where to begin? - Lutske de Leeuw (Craftsmen)
In this presentation, we will explore the fundamentals of machine learning and provide guidance on how to get started with building machine learning models. We will start by introducing machine learning and its applications, and then discuss the different types of machine learning algorithms.

We will then dive into the key steps involved in building a machine learning model, starting with defining the problem and collecting and preprocessing the data. We will discuss how to choose the right algorithm for the problem and optimize it for the best performance through model selection and training.

Throughout the presentation, we will provide examples of real-world applications of machine learning to help the audience understand the practical implications of this technology. We will conclude by summarising the key takeaways from the presentation and offering resources for further learning.

By the end of the presentation, the audience should have a good understanding of the basics of machine learning and the key steps involved in building an effective machine learning model. They will also have resources at their disposal to continue learning and exploring this exciting field.

About the speakers
Lutske de Leeuw is a Software Engineer at Craftsmen, currently working at DUO. A full-stack engineer with focus on Java and Angular. Loves machine learning, boardgames and cats. Wants to share knowledge, so everybody can benefit from it.

Tim te Beek is a staff software engineer at Moderne, which automates software refactoring at scale. He has extensive experience contributing to and presenting on Open Source software within the Java ecosystem. Previously he worked as a consultant specialising in migration engineering and developer productivity.