Data Science Austria

Comparing common analysis strategies for repeated measures data

Dealing with dependencies in data. What is this all about? My hope with this post is to provide a conceptual overview of how to deal with a specific type of dataset commonly encountered in the social sciences (and very common in my own disciplines of experimental psychology and cognitive neuroscience). My goal … Read moreComparing common analysis strategies for repeated measures data

What to do when your data fails OLS Regression assumptions

Regression analysis falls in the realm of inferential statistics. Consider the following equation: y ≈ β0 + β1x + e The approximate equals sign indicates that there is an approximate linear relationship between x and y. The error e term indicates this model isn’t going to fully reflect reality via … Read moreWhat to do when your data fails OLS Regression assumptions

Progressively-Growing GANs

The Progressively-Growing GAN architecture released from NVIDIA and published at ICLR 2018 has become the primary display of impressive GAN image synthesis. Classically, GANs have struggled to output low- and mid- resolution images such as 32² (CIFAR-10) and 128² (ImageNet), but this GAN model was able to generate high-resolution facial … Read moreProgressively-Growing GANs

Using Machine Learning to Identify the Minerals in Meteorites

How Meteorites are Studied The scientists scan meteorites using an electron microprobe (EMP). An EMP shoots a beam of electrons at the meteorite. When the beam of electrons collides with the atoms in the meteorite, the atoms emit x-rays. Each element has a distinct, characteristic frequencies. A graph of characteristic frequencies … Read moreUsing Machine Learning to Identify the Minerals in Meteorites

Review: MultiChannel — Segment Colon Histology Images (Biomedical Image Segmentation)

Foreground Segmentation using FCN + Edge Detection Using HED + Object Detection Using Faster R-CNN Gland Haematoxylin and Eosin (H&E) stained slides and ground truth labels Foreground Segmentation using FCN + Edge Detection Using HED + Object Detection Using Faster R-CNN In this story, MultiChannel is briefly reviewed. It is a Deep MultiChannel … Read moreReview: MultiChannel — Segment Colon Histology Images (Biomedical Image Segmentation)

RTX 2060 Vs GTX 1080Ti in Deep Learning GPU Benchmarks: Cheapest RTX vs. Most Expensive GTX card.

Less than a year ago, with its GP102 chip + 3584 CUDA Cores + 11GB of VRAM, the GTX 1080Ti was the apex GPU of last-gen Nvidia Pascal range (bar the Titan editions).The demand was so high that retail prices often exceeded $900, way above the official $699 MSRP. In … Read moreRTX 2060 Vs GTX 1080Ti in Deep Learning GPU Benchmarks: Cheapest RTX vs. Most Expensive GTX card.

Understanding Semantic Segmentation with UNET

A Salt Identification Case Study Table of Contents: Introduction Prerequisites What is Semantic Segmentation? Applications Business Problem Understanding the data Understanding Convolution, Max Pooling and Transposed Convolution UNET Architecture and Training Inference Conclusion References 1. Introduction Computer vision is an interdisciplinary scientific field that deals with how computers can be made … Read moreUnderstanding Semantic Segmentation with UNET