monday Session List
A Smooth Ride: Online Car Buying and Selling at mobile.de
Ricardo Kawase, Marlene Hense
Best Practice, Career & Freelancing, Use CaseBuying or selling a car is a challenging task that requires a lot of difficult decision-making. We will reveal all the "under the hood" data products at mobile.de that support users in making the right decisions.
Beyond the basics: Contributor experience, diversity and culture in open source projects
Melissa Weber Mendonça
Community, Diversity & Inclusion, GovernanceIn this talk, we'll explore actions and assumptions about DEI and how they relate to volunteer work and open-source communities, how we can go beyond the basics when engaging new contributors, and improving a project's culture around inclusiveness and different axes of diversity.
Building a Sign-to-Speech prototype with TensorFlow, Pytorch and DeepStack: How it happened & What I learned
Steven Kolawole
Computer Vision, Neural Networks / Deep LearningBuilding an E2E working prototype that detects sign language meanings in images/videos and generate equivalent voice of words communicated by the sign language, in real-time, won't be completed in a day's work. Here I'd explain how it happened and what I learned in the process.
Building an ORM from scratch
Jonathan Oberländer, Patrick Schemitz
Art, DatabasesFrom an empty Python file to a fully-featured ORM in 45 minutes
Career Panel
Katharine Jarmul, Matteo Guzzo, Sieer Angar, Marielle Dado, Emily Gorcenski
Career & FreelancingAre you thinking about a career change? In our career panel we will discuss different aspects with participants from different fields.
Creating 3D Maps using Python
Martin Christen
GIS / Geo-AnalyticsCreate 3DMaps anywhere on the planet using Python and OpenData
Data Apis: Standardization of N-dimensional arrays and dataframes
Stephannie Jimenez Gacha
APIsIntroduction to the consortium of Data APIs, where we will be presenting our motivation, objectives and progress of the standardization process after one year of activity.
Fundamentals of relational databases
Katharina Rasch
DatabasesSomewhat comfortable with using SQL to access data, but curious to know what happens behind the scenes when you send off your query?
Impact of Cultivating a Diverse and Inclusive Workplace
Riya Bansal
Community, Diversity & InclusionLet’s face it. The positive impact of diversity and inclusion is no longer debatable.
Inpsect and try to interpret your scikit-learn machine-learning models
Guillaume Lemaitre
Predictive Modelling, Statistics, Transparency / InterpretabilityInspect and try to interpret your scikit-learn machine-learning models
Introducing the Dask Active Memory Manager
Guido Imperiale
Algorithms, Architecture, Backend, Cloud, Data Engineering, Distributed Computing, Parallel Programming / AsyncThe Active Memory Manager is a new experimental feature of Dask which aims to reduce the memory footprint of the cluster, prevent hard to debug out-of-memory issues, and make worker retirement more robust.
Introduction to Uplift Modeling
Dr. Juan Orduz
Algorithms, Predictive Modelling, StatisticsIn this talk we introduce uplift modelling, a method to estimate conditional average treatment effects (CATE) using machine learning estimators.
Processing Open Street Map Data with Python and PostgreSQL
Travis Hathaway
Data Engineering, Databases, GIS / Geo-AnalyticsOpen Street Map is a large, community supported data set covering the entire world. Learn how to process this data with Python and PostgreSQL as I walk you through creating projects of your own. Along the way, we learn how OSM data is structured, and how you can use it yourself.
pytest - simple, rapid and fun testing with Python (3 hours)
Florian Bruhin
Best Practice, Development MethodsThe #pytest tool presents a rapid and simple way to write tests for your Python code. This training gives an introduction with exercises to some distinguishing features.
Python 3.10: Welcome to pattern matching!
Laysa Uchoa
Best Practice, Coding / Code-Review, Python fundamentalsPython 3.10: let us learn about Pattern Matching. In this presentation, you will be surprised how simple, yet powerful, Pattern Matching really is. This talk and you, it is a match! 🔥
Rewriting your R analysis code in Python
Helena Schmidt
Best Practice, Development Methods, RR and Python are two of the most powerful tools for any kind of data analysis. But both programming languages have their strengths and weaknesses. This leads to the question: When and how to rewrite your R analysis code in Python?
Seeing the needle AND the haystack: single-datapoint selection for billion-point datasets
Jean-Luc Stevens
Big Data, Data Visualization, JupyterBuilding simple custom interactive web dashboards that display millions or billions of samples while giving access to each individual sample.
sktime - python toolbox for time series: advanced forecasting - probabilistic, global and hierarchical
Franz Kiraly
Algorithms, Predictive Modelling, Time SeriesThe forecasting module of sktime provides a unified, sklearn-compatible, and composable interface. This tutorial covers advanced topics in forecasting using sktime: probabilistic forecasting, and forecasting with panel data, including global/hierarchical forecasting.
The Myth of Neutrality: How AI is widening social divides
Stefanie Stoppel
Ethics (Privacy, Fairness,… ), Neural Networks / Deep LearningAI is not neutral and its creation often perpetuates harmful biases. My talk highlights how difficult it is to build "fair and responsible" AI, but also why it's worth to try & prevent these algorithms from cementing existing injustices.
The secret sauce of data science management
Shir Meir Lador
Best Practice, Big Data, Career & Freelancing, CorporateIn this talk, we will discuss lessons learned on how to build a DS team that prospers while addressing the unique challenges of leading a DS team.
Trojan Source Malware - Can we trust open-source anymore?
Cheuk Ting Ho
Community, Governance, Python fundamentals, Security, Transparency / InterpretabilityTrojan Source Malware has been tested on Python and it works. Shall the Python and open-source communities be concerned?
What I learned from monitoring more than 30 Machine Learning Use Cases
Lina Weichbrodt
Best Practice, Backend, DevOpsHow to implement #MachineLearning #monitoring for the impatient. Lessons I learned from running more than 30 models in production. And good news, you can use your existing monitoring and dashboard stack like #Prometheus and #Grafana
You shall not share!
Gönül Aycı
Ethics (Privacy, Fairness,… ), Natural Language ProcessingAre you ready to have an agent to help to preserve your privacy in online social networks? "You shall not share!" will be presented by @gonul_ayci ⚡️
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