Data Science Austria

Doing meaningful work with Machine Learning — Classify Disaster Messages

Build models to help disaster organizations save people’s lives. I’m writing this post at 1am in Bucharest, Romania. Hello there again! Welcome to my fourth piece of content about Machine Learning. I’ve recently done a project that I believe to be socially meaningful. I’ll give a brief overview what this is … Read moreDoing meaningful work with Machine Learning — Classify Disaster Messages

Reinforcement Learning: From Grid World to Self-Driving Cars

0. Agents, Environments, and Rewards Underlying many of the major announcements from researchers in Artificial Intelligence in the last few years is a discipline known as reinforcement learning (RL). Recent breakthroughs are mostly driven by minor twists on on classic RL ideas, enabled by the availability of powerful computing hardware and … Read moreReinforcement Learning: From Grid World to Self-Driving Cars

Supervised Learning: Basics of Classification and Main Algorithms

Introduction As stated in the first article of this series, Classification is a subcategory of supervised learning where the goal is to predict the categorical class labels (discrete, unoredered values, group membership) of new instances based on past observations. There are two main types of classification problems: Binary classification: The … Read moreSupervised Learning: Basics of Classification and Main Algorithms

What’s your soccer team’s nemesis?

Is Barcelona really Real Madrid’s toughest opponent? Historical data paint an interesting story. Image from unsplash.com Real Madrid vs Barcelona. Manchester United vs Liverpool. Inter vs Milan. Olympique Lyonnais vs Olympique de Marseille. Chelsea vs everybody. European soccer is filled with some amazing rivalries. These rivalries got created and evolved … Read moreWhat’s your soccer team’s nemesis?

The Danger of Artificial Intelligence in Recruiting (and 3 Suggestions)

I recently came across one of the most well-intended, and most unnerving, applications of AI in recruiting; a talking robot head pitched as a solution to avoid bias in interviewing. Picture a robot the size of an Alexa with an actual human face painted to the top. The face changes, … Read moreThe Danger of Artificial Intelligence in Recruiting (and 3 Suggestions)

Creation of Sentence Embeddings Based on Topical Word Representations

An approach towards universal language understanding I am researching on word and sentence embeddings for over a year now and recently wrote also my master’s thesis [1] in this area. The results which I am presenting now were also published here and resulted in cooperation with SAP and the University … Read moreCreation of Sentence Embeddings Based on Topical Word Representations

What I Learned from Writing a Data Science Article Every Week for a Year

3. Consistency is the critical factor The 98 articles I published in 2018 totaled 264,894 words. For every word published, there was at least 1 word that didn’t make it through editing. This works out to about 530,000 words or 1,500 words per day. The only way this was possible studying … Read moreWhat I Learned from Writing a Data Science Article Every Week for a Year