Data Science Austria

A Chance to Get it Right: Embracing Automated Decision Making

franki chamak for unsplash Diminishing Bias with ADM It is with a sort of helpless resignation that we have spent so many decades bearing witness as imbalanced power, wealth, and race and gender dynamics have skewed access to our most fundamental basic rights: freedom, liberty, the pursuit of happiness, jobs, and even … Read moreA Chance to Get it Right: Embracing Automated Decision Making

Time to program guardians to protect ourselves: AI experts

Computers are increasingly using our data to make decisions about us, but can we trust them? Daily, without your knowledge, computer algorithms are using your data to predict your habits, preferences and behaviour. They decide your love of YouTube cat videos means you’ll be spammed by Whiskers ads, or that your … Read moreTime to program guardians to protect ourselves: AI experts

Variational Autoencoder In Finance

Part 1: Dimensionality Reduction Using a Variational Autoencoder In this section, we will discuss: Creating the geometric moving average dataset Augmenting the data with stochastic simulation Building the variational autoencoder model Obtaining the predictions. Creating The Geometric Moving Average Dataset In order to compare time series of various price ranges, … Read moreVariational Autoencoder In Finance

Thunderstruck: Disaster CNN visualization of AC power lines

NET Centre at VŠB is trying to detect partial discharge patterns from overhead power lines by analyzing power signals. This Kaggle challenge was a fun one for any electrical power enthusiasts. Ideally, we would be able to detect the slowly increasing damage to the power lines before it suffers a … Read moreThunderstruck: Disaster CNN visualization of AC power lines

Mathematical programming — a key habit to built up for advancing in data science

Introduction The essence of mathematical programming is that you build a habit of coding up mathematical concepts, especially the ones involving a series of computational tasks in a systematic manner. This kind of programming habit is extremely useful for a career in analytics and data science, where one is expected … Read moreMathematical programming — a key habit to built up for advancing in data science

Interactive Data Visualization with Vega

Building a timeline with Vega A timeline built with Vega Some Vega properties we’ll use to build the timeline 1 — 🗂 “data”: [] Besides loading the data we can also filter, calculate new fields or derive new data streams using Vega Transforms. We can sort the items by name using the collect transform: “data”: [{“name”: … Read moreInteractive Data Visualization with Vega

10 Tips to build a better modeling dataset for tree-based machine learning models

To make the model more accurate — simply one-hot encode all categorical features and impute all missing values with zero may not be enough. Silver Lake, Utah (photo by my wife, Yi) Assuming there’s a business problem that can be converted to a machine learning problem with tabular data as its input, clearly defined … Read more10 Tips to build a better modeling dataset for tree-based machine learning models