10 Years of Automated Category Classification for Product Data
Johannes Knopp
Artificial Intelligence, Deep Learning, Data Science, Infrastructure, Machine Learning, Data Engineering

10 years ago we built a classifier for categorizing product data. Let's take a journey through the lessons we learned over the years about building, maintaining, and modernizing the category classifier.

Algo.Rules - How do we get the ethics into the code?
Carla Hustedt
Algorithms

Algo.Rules - How do we get the ethics into the code? 9 rules for the design of algorithmic systems

Applying deployment oriented mindset for building Machine Learning models
Marianna Diachuk
Data Science, Machine Learning

Getting stuck for months trying to deploy the model and fighting with data inconsistency and bugs? This talk will introduce the way to build the development process with deployment in mind.

Are you sure about that?! Uncertainty Quantification in AI
Florian Wilhelm
Artificial Intelligence, Deep Learning, Data Science, Machine Learning, Science

Are you sure about that?! Uncertainty Quantification in AI helps you to decide if you can trust a prediction or rather not.

Commenting code — beyond common wisdom
Stefan Schwarzer
Code-Review

Good code comments are important for software maintenance. This talk goes beyond the common wisdom you find in most books and online and explains when this common wisdom falls short.

Data Literacy for Managers
Alexander CS Hendorf
Artificial Intelligence, Business & Start-Ups, Data Science, Machine Learning, Use Cases

Artificial Intelligence need to be better understood in enterprises. Close the communications gap between engineers and management. Making data litteracy happen in your organisation.

Event-Sourced Story
Jacek Kołodziej
Use Cases

Basics and three years of experience in utilizing event sourcing in a real-life application with its ups and downs - come hear the Event-Sourced Story.

Extended Ligthning Talks CANCELLED: Crunching Numbers Like a Journalist
Marie-Louise Timcke
Big Data, Data Science, Statistics

Marie will talk about how newsrooms work with data on a day to day basis, and how scientific accuracy fits in with the pace of news reporting.

From body and code <programming in times of acceptance>
Paloma
Business & Start-Ups, Community, Web

What does diversity means? Social justice YES \o/ but also to reclaim knowledge & critical perspective | #diversity #criticalDisability #inclusion

Hidden Markov Models for Chord Recognition - Intuition and Applications
Caio Miyashiro
Algorithms, Data Science, Machine Learning, Statistics

Come check out Caio's workshop on music+programming+stats on PyData

How MicroPython went into space
Christine Spindler
Microcontrollers

MicroPython used in space as an On Board Control Procedure (OBCP) engine

How strong is my opponent? Using Bayesian methods for skill assessment
Darina Goldin
Algorithms

Introduction to the ranking algorithms Elo, Glicko2, and Trueskill.

Job Panel
Christian Barra, Tereza Iofciu, Katharina Rasch, Matteo Guzzo, Sieer Angar
Business & Start-Ups

A panel about freelancing & moving from academia to industry

Kartothek – Table management for cloud object stores powered by Apache Arrow and Dask
Florian Jetter
Big Data, Data Engineering

Kartothek - Table management for cloud object stores powered by @ApacheArrow and @dask_dev

Law, ethics and machine learning – a curious ménage à trois
Dr. Benjamin Werthmann
Artificial Intelligence, Big Data, Machine Learning

Find out and discuss how law and ethics should be included in a framework for machine learning that protects creativity and effectiveness

Lessons Learned as a Product Manager in Data Science
Tereza Iofciu
Business & Start-Ups, Data Science, Machine Learning

How many languages does the data science product manager need to speak?

Loss Function Theory 101
David Wölfle
Artificial Intelligence, Algorithms, Deep Learning, Data Science, Machine Learning, Statistics

This talk covers the theoretical background behind two common loss functions, mean squared error and cross entropy, including why they are used for machine learning at all, and what limitations you should keep in mind.

Optimizing Input: Building your own customized keyboard
Daniel Rios
Community, Microcontrollers, Makers

Optimizing input by building your own keyboard. Learn where the modern keyboard originated and what the present holds for the future of text input.

Professional Development and Career Progression for Data Scientists
Noa Tamir
Business & Start-Ups, Community, Data Science

How to level up your skills and develop your your career by making the most of on the job opportunities, as well as open source contributions

Rethinking Open Source in the Era of Cloud & Machine Learning
Peter Wang
Python

Open Source is a wildly successful and crucial part of many areas of modern technology. However, the ’sustainability crisis’ and the age of cloud computing have threatened its core mechanisms.

Static Typing in Python
Dustin Ingram
Science

In this talk, we'll discuss the advantages and disadvantages to a static type system

Tackle the problems that really matter - leverage the power of data science in the service of humanity
Eva Schreyer, Lisa Zäuner
Business & Start-Ups, Community, Data Science

We talk about how DSSG @dssgber brings together data scientist volunteers and non-profit organisations to tackle their data challenges in various events.

The Sound of Silence: Online Misogyny and How we Model it
Teresa Ingram
Community, Natural Language Processing, Machine Learning

Opt Out of Online Sexism - From a Problem to Open Source Activism and the Mechanics of Change

Tools that help you get your experiments under control
Katharina Rasch
Artificial Intelligence, Data Science, DevOps, Infrastructure

There is now a wealth of tools that support data science best practices (e.g. tracking experiments, versioning data). Let’s take a look at which tools are available and which ones might be right for your project.

Want to have a positive social impact as a data scientist?
Ellen König
Community, Data Science

Find your individual approach towards more positive social impact by conducting experiments! I'll show you how.

What if I tell you that your specs are broken
Samuele Maci
Networks

"What if I tell you that your specs are broken". Protect your specs against incompatible changes ... a practical guide

What we learned from scraping 1 billion webpages every month
Samet Atdag
Business & Start-Ups, Big Data, Infrastructure, Web, Data Engineering

We broke the web via simple hacks. Instead of order, we caused chaos. How to fix that?

Where Linguistics meets Natural Language Processing
Mariana Capinel
Natural Language Processing

This talk explains how linguistics describes language - via phonetics-phonology, morphology, syntax, semantics and pragmatics. We will combine linguistic concepts with models through examples for NLP newbies.

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