Data Science Austria

Connections, connections, and connections… Social media is used every day for many purposes: expressing opinions about different topics such as products and movies, advertising an event, a service or a conference, among other things. But what is most interesting about social media, and particularly for this post, about Twitter, is

This is it. This is the best goddamn thing I’ve ever done. I don’t normally like to brag but I’m so freak’n proud of myself for this one that I feel like I need to share it. They said it wasn’t possible (no one actually said that), they said it

Basic medical imaging terminology Magnetic resonance imaging (MRI) is a cross-sectional imaging modality, meaning that 2D images are acquired more-or-less sequentially in different imaging planes. The standard planes of imaging included in the MRNet data set are: axial, coronal and sagittal. MR images can be acquired in any plane, but

This article is meant to be a high-level overview of the work Jeff Woo and I did for our CS 224N final project at Stanford. The paper and poster are available for those interested in diving further into the technical details of our work. Background and Dataset Russian trolls used social

Results Congratulations! You made it through the tough technical part. Now you wanna see results, right? Looks brilliant, right? Okay, you got me. The table doesn’t look brilliant yet, right? Nonetheless, it’s worth mentioning what happened here. Basically, I learned the (324,6)-Q-table over 5,000,000 steps and “tested” it by predicting

Software development: best practices in a deep learning environment Deep learning systems are now being used extensively in many environments. They differ from traditional software systems in the manner through which output is generated: decisions which are made to produce results are learned from training data, rather than being hand-coded,

Comprehensive Introduction to Autoencoders By Matthew Stewart, PhD Researcher — 15 min read In the following weeks, I will post a series of tutorials giving comprehensive introductions into unsupervised and self-supervised learning using neural networks for the purpose of image generation, image augmentation, and image blending.

In conjunction with other global trends, Artificial Intelligence is rapidly tearing down the old barriers to building new world orders. As a result the next century will be dominated by countries that rapidly adapt to the new AI Economy. The assumptions that the next century will be the “Chinese Century”