wednesday-14:00 Session List

Talk pydata-pydata-scientific-libraries-stack

5 Steps to Speed Up Your Data-Analysis on a Single Core

Jonathan Striebel

Data Engineering, Performance

Your data analysis pipeline works. Nice. Could it be faster? Probably. Do you need to parallelize? Not yet. Discover optimization steps that boost the performance of your data analysis pipeline on a single core, reducing time & costs.

Talk pydata-deep-learning

Financial Portfolio Management with Deep Reinforcement Learning

T-Berger

Neural Networks / Deep Learning, Simulation, Time Series

intelligent_portfolio_optimization_with_deep_reinforcement_learning

Talk pycon-programming-software-engineering

How to Find Your Way Through a Million Lines of Code

Jürgen Gmach

Best Practice

Scared of a new project? @jugmac00 will show you "How to Find Your Way Through a Million Lines of Code"

Tutorial pydata-machine-learning-stats

Making MLOps uncool again

David

Best Practice, Development Methods, Reproducibility

In this workshop, we will learn what it means and how to build an "MLOps workflow" by extending the power of Git and GitHub with open-source tools.

Talk pydata-natural-language-processing

Performing Content: Can NLP and Deep Learning algorithms predict reader preferences?

Sebastian Cattes

Natural Language Processing, Neural Networks / Deep Learning, Statistics

Can AI understand what drives user engagement? Join our talk "Performing Content: Can NLP and Deep Learning algorithms predict reader preferences?" to find out what NLP can bring to the editorial table.

Tutorial pydata-deep-learning

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 🤩