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Title & Speakers	Event
Event Members Talk Evening [in person and streamed] 2023-07-11
How to be a good reviewer: Be honest, nice, and a badass 2023-07-11 · 20:00 Raana Saheb Nassagh – Intermediate Python developer The first time I was asked to review a colleague's code, I was unsure: What was expected of me? What exactly was I supposed to check? And, most importantly, wouldn't I make myself unpopular by pointing out others' mistakes? In my presentation, I will describe what I have learned since then. Using real examples, I’ll point out what you should look for when reviewing code (e.g. readability, redundancy, files & data), which tools you can use (e.g. gitlab runner, black, mypy) and how to stay friends while being brutally honest with each other :-) By the way: The examples of code bugs are not only from my colleagues. After all, my own code is constantly reviewed and fixed by others. And yes, I admit, it hurts every single time… Python gitlab runner black mypy
Modeling mental hops from one word to the next with NLP and Python 2023-07-11 · 19:20 Tamara Atanasoska – Open Source Software Engineer @ :probably.. How would you model the mental hops that lead from one word to the next? And how about when instead of a word, the starting point are concepts grounded explicitly or implicitly in an image? These questions, and more, were the topic of my latest research project. Working to automatically generate image-term pairs for an image-grounded, collaborative Wordle game, I looked for combinations that spark the desired type of dialogue - illuminating the participants' decision-making. The project fits the broader efforts toward natural language explainability that Prof. Schlangen’s research group at the University of Potsdam is undertaking. We will look at the method I developed from an engineering perspective, going over all the NLP concepts composing it, and touch upon a bit of linguistics theory too. Level: Beginner to the domain (already familiar with Python) Python NLP

Event Members Talk Evening [in person and streamed] 2023-06-27
Klea Sanka - The World of Salary: Introducing Salary Prediction Models at StepStone 2023-06-27 · 20:15 Klea Sanka – Data Scientist @ StepStone GmbH This presentation explores the salary landscape in the German job market, focusing on the challenges of data collection and approaches used to analyse it. We will discuss the importance of getting just the right features and how to balance the amount of data used. We will also examine the pipeline from experimentation to production models and the importance of keeping track of metrics and how we can automatise the process. Lastly, we will delve into the challenges of gender bias, data representation, and monotonicity, looking at how these factors impact our predictions, as well as prospects for future work. Python cloud platforms
Maren Westermann - How to increase diversity in open source communities 2023-06-27 · 19:30 Maren Westermann – scikit-learn team member @ PyLadies Berlin Today state of the art technology and scientific research strongly depend on open source libraries. The demographic of the contributors to these libraries is predominantly white and male. This situation creates problems not only for individual contributors outside of this demographic but also for open source projects such as loss of career opportunities and less robust technologies, respectively. In recent years there have been a number of various recommendations and initiatives to increase the participation in open source projects of groups who are underrepresented in this domain. While these efforts are valuable and much needed, contributor diversity remains a challenge in open source communities. This talk highlights the underlying problems and explores how we can overcome them. open source libraries scikit-learn

How to be a good reviewer: Be honest, nice, and a badass 2023-07-11 · 20:00

Raana Saheb Nassagh – Intermediate Python developer

The first time I was asked to review a colleague's code, I was unsure: What was expected of me? What exactly was I supposed to check? And, most importantly, wouldn't I make myself unpopular by pointing out others' mistakes? In my presentation, I will describe what I have learned since then. Using real examples, I’ll point out what you should look for when reviewing code (e.g. readability, redundancy, files & data), which tools you can use (e.g. gitlab runner, black, mypy) and how to stay friends while being brutally honest with each other :-) By the way: The examples of code bugs are not only from my colleagues. After all, my own code is constantly reviewed and fixed by others. And yes, I admit, it hurts every single time…

Python gitlab runner black mypy

Modeling mental hops from one word to the next with NLP and Python 2023-07-11 · 19:20

Tamara Atanasoska – Open Source Software Engineer @ :probably..

How would you model the mental hops that lead from one word to the next? And how about when instead of a word, the starting point are concepts grounded explicitly or implicitly in an image? These questions, and more, were the topic of my latest research project. Working to automatically generate image-term pairs for an image-grounded, collaborative Wordle game, I looked for combinations that spark the desired type of dialogue - illuminating the participants' decision-making. The project fits the broader efforts toward natural language explainability that Prof. Schlangen’s research group at the University of Potsdam is undertaking. We will look at the method I developed from an engineering perspective, going over all the NLP concepts composing it, and touch upon a bit of linguistics theory too. Level: Beginner to the domain (already familiar with Python)

Python NLP

Klea Sanka - The World of Salary: Introducing Salary Prediction Models at StepStone 2023-06-27 · 20:15

Klea Sanka – Data Scientist @ StepStone GmbH

This presentation explores the salary landscape in the German job market, focusing on the challenges of data collection and approaches used to analyse it. We will discuss the importance of getting just the right features and how to balance the amount of data used. We will also examine the pipeline from experimentation to production models and the importance of keeping track of metrics and how we can automatise the process. Lastly, we will delve into the challenges of gender bias, data representation, and monotonicity, looking at how these factors impact our predictions, as well as prospects for future work.

Python cloud platforms

Maren Westermann - How to increase diversity in open source communities 2023-06-27 · 19:30

Maren Westermann – scikit-learn team member @ PyLadies Berlin

Today state of the art technology and scientific research strongly depend on open source libraries. The demographic of the contributors to these libraries is predominantly white and male. This situation creates problems not only for individual contributors outside of this demographic but also for open source projects such as loss of career opportunities and less robust technologies, respectively. In recent years there have been a number of various recommendations and initiatives to increase the participation in open source projects of groups who are underrepresented in this domain. While these efforts are valuable and much needed, contributor diversity remains a challenge in open source communities. This talk highlights the underlying problems and explores how we can overcome them.

open source libraries scikit-learn

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