DIKU Talk by Dr. Kévin Allix: Before Machine-Learning: Storing, Reading, and Processing Data

Summary

Machine-Learning attracts a lot of attention, almost eclipsing the fundamental steps required to feed Machine-Learning with vast quantities of Data. In this lecture, we will cover several aspects of modern Data pipelines, including Data acquisition, Storage, Querying, and Representation. Each of these steps carry its very own difficulties, is supported by a wide variety of tools and methods, and requires practitioners to select the optimal trade-off for their applications. We will discuss some of these trade-offs, and put them in perspective with the many (*many*) tools that are part of the "Data" ecosystem.

Bio

Dr. Kévin Allix portraitDr. Allix is a Research Associate at the SnT Interdisciplinary Center of the University of Luxembourg, where he obtained his PhD in 2015. His research interests are Android Malware Detection, Machine Learning, Automatic Document Processing and Natural Language Processing. Previously, he held operational positions as system, network, and security engineer.

The talk is being held on Zoom. To join, please click here.