Corrie BartelheimerData Science, Statistics
An Example of a Bayesian Workflow using PyMC and ArviZ: Predicting House Prices in Berlin
Did you know that a DSL with variables and recursion was invented when people were still building castles? This DSL describes exactly how to paint a coat of arms. Learn how to write a parser for it, and the tools to make your own DLS
Oliver BestwalterAlgorithms, Code-Review, APIs, Use Cases
Abridged metaprogramming classics - this episode: pytest. About the role of metaprogramming in the creation of a simple to use but powerful testing framework.
Valentin HaenelAlgorithms, Big Data, Data Science, Parallel Programming
Learn to program GPUs (e.g. Kernels) in Python with CuPy and Numba.
Dmitry NazarovWeb, Use Cases
This @edgedatabase talk will cover both the basics (setup, syntax, repl, simple usecase) as well as advanced topics (indexes, performance, complex usecases). We'll also talk history of databases as is
Peter Kairouz, Amlan ChakrabortyArtificial Intelligence, Deep Learning, Data Science, Machine Learning, Data Engineering
Meet TensorFlow Federated: an open-source framework for machine learning and other computations on decentralized data.
Andrada PumneaDeep Learning, Data Science, Natural Language Processing, Data Mining / Scraping
Does hate sound the same in all languages? Join this talk to learn more about hate speech detection in a language less circulated, from dataset creation to hate speech recognition model..
Gina HäußgeWeb, 3D Priniting, Makers
OctoPrint is an open source web interface for 3D printers and deployed world wide on a large variety of devices. Learn about some of the challenges in developing and maintaining such a piece of end user facing software in Python
Jacek KołodziejUse 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.
Yuta KanzawaData Science, Machine Learning, Visualisation, Statistics
R and Python are different in community and as language. Still, comparing them in their common fields such as data wrangling and visualisation, useRs and Pythonistas will deepen mutual understanding.
Alexander EngelhardtData Science, Machine Learning
In this talk, we'll find out how to interpret the predictions of otherwise black-box models.
Raphael PierzinaDevOps, Web, Data Engineering
Learn how to get started with developing automated tests in Python with the pytest test framework!
Christian Barra, Tereza Iofciu, Katharina Rasch, Matteo Guzzo, Sieer AngarBusiness & Start-Ups
A panel about freelancing & moving from academia to industry
Dr. Benjamin WerthmannArtificial 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
Tereza IofciuBusiness & Start-Ups, Data Science, Machine Learning
How many languages does the data science product manager need to speak?
Korbinian KuusistoAlgorithms, Business & Start-Ups, Data Science, Machine Learning, Science, Statistics
How can one leverage the power of Bayesian methods to build a successful data science product?
David WölfleArtificial 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.
Andreas HantschDeep Learning, Machine Learning, Science
This talk is about the coupling of a digital twin model and a machine learning predictive maintenance algorithm in order to be able to detect anomalies in the operation of a not well-known hardware system.
Tania VasilikiotiData Science, Visualisation
Creating graphics that convey the desired message, are easily interpretable, but also beautiful can be a daunting task. Come to this talk to learn how to use The Grammar of Graphics to make any complex graphic simple, in Python.
Tobias SterbakData Science, Infrastructure, Machine Learning, Data Engineering
How to manage the end-to-end machine learning lifecycle with MLflow.
Hari Kishore SirivellaDjango, DevOps, Infrastructure
Monitoring infrastructure and application using Django, Sensu and Celery.
Daniel RiosCommunity, 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.
Dominik Henter, Jéssica LinsInfrastructure, Networks, Parallel Programming
A tutorial about parallel programming in Go, from the perspective of a Python developer.
Noa TamirBusiness & 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
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.
Patrick ArminioDjango, Web
Strawberry is a code-first GraphQL library that makes use of dataclasses and type hints.
Peggy Sylopp, Aislyn RoseArtificial Intelligence, Algorithms, Computer Vision, Deep Learning, Data Science, Machine Learning, Science
Control what you hear with deep learning and open audio databases. The developer and manager of \\NoIze//, a project supported by Prototype Fund, share what’s helped them build an open source smart, low-computational noise filter in Python.
Teresa IngramCommunity, Natural Language Processing, Machine Learning
Opt Out of Online Sexism - From a Problem to Open Source Activism and the Mechanics of Change
Avaré StewartArtificial Intelligence, Data Science, Natural Language Processing, Machine Learning, Data Engineering
Unleash Intelligence in you Data Transform a Legacy System into Bias-Mitigating AI Solution for Debt Repayment with Tesseract, SpaCy, & AI Fairness 360
Filipe SilvaData Science, Machine Learning
Using machine learning models for level generation in video-games
Alessia MarcoliniArtificial Intelligence, Data Science, Machine Learning
Versioning in Data Science projects can be pretty painful: are you able to track the data sets along with the code itself and some of the resulting models?
Samet AtdagBusiness & 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?
What’s new in Python 3.8? Learn the new features of this new version
Yurii TolochkoArtificial Intelligence, Algorithms, Deep Learning, Machine Learning, Statistics
Why doesn’t RL show the same success as (un)supervised learning? Inherent difficulties facing RL and avenues for future work
Miroslav ŠedivýAlgorithms, Community, Natural Language Processing, Web, Data Mining / Scraping, Use Cases
If your code tells me “Your Name Is Invalid!”, then your code is probably invalid. Names of people cannot be invalid.