Xander Steenbrugge

Head of applied Machine Learning research at ML6

Xander is a computer-science engineer from Belgium, Europe, fascinated by Machine Learning and Artificial Intelligence and YouTube vlogger at ‘Arxiv Insights’. Through his master thesis on EEG-based brain-computer interfaces, Xander first came into contact with the vast opportunities provided by data driven computer algorithms. Working as a Machine Learning consultant for 4 years, Xander has worked on many different projects including computer vision (object tracking, optical character recognition, image classification, ..) , natural language processing (chatbots, text classification, …) and many others using open source libraries like TensorFlow and Pytorch in combination with powerful compute resources on the Google cloud platform.Recently, Xander started focussing on the interface between academic research and the real world through a PhD in Deep Reinforcement Learning focussed on applying these novel algorithms to industrial process optimization. Xander is now head of applied ML-research at Belgian AI scale-up ML6.


Building your first intelligent agent to play video games, using Reinforcement Learning and PyTorch!   Reinforcement Learning is transforming the AI landscape by allowing neural network based ‘intelligent agents’ to interact with dynamic environments, achieving goals through autonomous learning. In this hack session we will build a simple neural net agent with PyTorch and train […]

09:00 am - 12:30 pm

Building your first intelligent agent to play video games, using Reinforcement Learning and PyTorch!


GETTING STARTED WITH DEEP LEARNING Do you want to jump into the Deep Learning bandwagon? Are you still stuck on grasping how backpropagation works? Then this workshop is for you! The goal of this workshop is to get you up to speed with the advancements in Deep Learning with a practical perspective.   Along with […]

09:00 am - 06:00 pm

Workshop1: Applied Machine Learning, Workshop2: The MasterClass, Workshop3: Computer Vision Using Pytorch, Workshop4: Machine Learning at Scale Using SparkML for Big Data, Workshop5: Getting started with Natural Language Processing, Workshop6: Getting started with Deep Learning

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