"Easy Python": lies, damned lies, and metaclasses
Grigory Petrov, Maxim Danilov
Best Practice, Coding / Code-Review, Development Methods

top-10 Python complexities and how they are required to fight the "software complexity problem" in big projects

Advanced Django ORM
Bas Steins
Databases, Django

Leverage the potential of Django ORM to write complex queries, optimize performance and have fun with constraints

Biases in Language Models
Diversity & Inclusion, Ethics (Privacy, Fairness,… ), Natural Language Processing

Study of gender biases in popular language models and debiasing model techniques

Building an ORM from scratch
Jonathan Oberländer, Patrick Schemitz
Art, Databases

From an empty Python file to a fully-featured ORM in 45 minutes

Making Machine Learning Applications Fast and Simple with ONNX
Jan-Benedikt Jagusch, Christian Bourjau
Data Engineering, DevOps, Packaging

In this session, you will learn how to use ONNX for your machine learning model deployments, which can reduce your single-row inference time by up to 99% while also drastically simplifying your model management.

Navigating the limitations of Python’s concurrency model in web services
Tarek Mehrez
APIs, Architecture, Parallel Programming / Async

Ever wondered when you should favor an async web framework? How do they compare to your good old python services when scaling is in question? Then this is the talk for you

PPML: Machine Learning on Data you cannot see
Valerio Maggio
Neural Networks / Deep Learning, Security

Have you ever wondered how to train your @PyTorch model on private data you cannot see? If you want to know how, this is the workshop for you! #PPML cc/ @openminedorg

Practical graph neural networks in Python with TensorFlow and Spektral
Aleksander Molak
Graphs, Neural Networks / Deep Learning

Practical Graph Neural Networks (GNNs) with Spektral & TensorFlow 🤩

Python 3.11 in the Web Browser - A Journey
Christian Heimes
Python - CPython new features

Compile CPython to Web Assembly, and run it in web browsers or Node.js.

Squirrel - Efficient Data Loading for Large-Scale Deep Learning
Dr. Thomas Wollmann
Distributed Computing, Neural Networks / Deep Learning, Parallel Programming / Async

Learn why we built and open sourced a data infrastructure library for deep learning.