A (very brief) Overview of Deep Learning and its Open Source Tools
Speaker: Noud Aldenhoven
Due to the massive amount of digital data which became available last few years, deep learning techniques have been flourishing in artificial intelligence. Some tasks that a computer couldn't solve at all ten years ago, are now solved on your smartphone without many problems, e.g. image classification, language translation, playing go, cancer detection. Deep learning techniques appear to be very successful solving these tasks, yielding human or even super human performance.
In this talk, I will give a (very brief) overview of deep learning and its applications. Understanding the differences between classical machine learning and modern deep learning, I explain what deep learning is and how it works. An overview of some of the open source deep learning tools is given, e.g. Caffe, Torch, Tensorflow, etc.
I assume some familiarity with linear algebra, and elementary calculus.
Noud Aldenhoven has a master's degree in mathematics, and he obtained a PhD in mathematical physics in 2015 at the Radboud University Nijmegen.
After his PhD he started as data scientist at Screenpoint Medical in Nijmegen, a young company that develops image analysis technology for automated reading of mammograms and digital breast tomosynthesis.
Besides his interests in mathematics, computer science, and data science, Noud is a fanatic athlete. He enjoys his free time, swimming, cycling, and running.