Any machine learning algorithm needs hyperparameters to define how the algorithm learns from your data and how the model looks like. These hyperparameters can have a large impact on how good the model learns from your data and how well it performs on data it has never seen before.
The optimization of these hyperparameters is often a time-intensive and computationally hard process. In the next Rootlabs @ Lunch, Hans Tierens explains several different approaches on how we can optimize and automate this process, so we can build better machine learning models in no time.
He will give an overview on what we need, how we need it, when we need it and how we can start doing it now!
This event is open to anyone and is organised by the machine learning guild in dataroots, which invests time and resources in research.
The link to the live stream: https://youtu.be/lZYcQ9XpRF0
How can we help?
The Leuven MindGate team is at your disposal for any questions about the Leuven Innovation Region. Do you want to invest, work or study in the region? We can help you find your way.
We also facilitate collaboration and innovation between companies, knowledge institutes and government within the Leuven Innovation Region, and we are happy to guide any of these stakeholders towards innovation.