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Event: PyData Berlin 2023
Other events in this series:
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2015
2016
2017
2018
2019
2023
A concrete guide to time-series databases with Python
A journey through 4 industries with Python
Accelerating Public Consultations with Large Language Models
Actionable Machine Learning in the Browser with PyScript
Advanced Visual Search Engine with Self-Supervised Learning (SSL)
Apache Arrow - Connecting and accelerating dataframe libraries across the PyData
Apache StreamPipes for Pythonistas: IIoT data handling made easy!
Ask-A-Question - an FAQ-answering service for when there's little to no data
AutoGluon - AutoML for Tabular, Multimodal and Time Series Data
Bayesian Marketing Science - Solving Marketing's 3 Biggest Problems
BHAD - Explainable unsupervised anomaly detection using Bayesian histograms
Building a personal internet front-page with spaCy and Prodigy
Common issues with Time Series data and how to solve them
Contributing to an open-source content library for NLP
Cooking up a ML Platform - Growing pains and lessons learned
Create interactive Jupyter websites with JupyterLite
Delivering AI at Scale
Driving down the Memray lane - Profiling your data science work
Dynamic pricing at Flix
evosax - JAX-Based Evolution Strategies
Exploring the Power of Cyclic Boosting
Geospatial Data Processing with Python - A Comprehensive Tutorial
Getting started with JAX
Haystack for climate Q/A
How Are We Managing? Data Teams Management IRL
How Chatbots work – We need to talk!
How Python enables future computer chips
How to baseline in NLP and where to go from there
How to build observability into a ML Platform
How to Feed Facts to Large Language Models and Reduce Hallucination
How to Optimize Infrastructure, Tools and Teams for ML Workflows
How to teach NLP to a newbie & get them started on their first project
Hyperparameter optimization for the impatient
I broke the PyTorch model - Debugging custom PyTorch models in a structured manner
Improving Machine Learning from Human Feedback
Incorporating GPT-3 into practical NLP workflows
Large Scale Feature Engineering and Datascience with Python & Snowflake
Let's contribute to pandas (3 hours) PART.1
Let's contribute to pandas (3 hours) PART.2
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Methods for Text Style Transfer - Text Detoxification Case
Most of you don't need Spark. Large-scale data management on a budget with Python
Neo4j graph databases for climate policy
Observability for Distributed Computing with Dask
Pandas 2.0 and beyond
Performing Root Cause Analysis with DoWhy, a Causal Machine-Learning Library
Polars - make the switch to lightning-fast dataframes
Postmodern Architecture - The Python Powered Modern Data Stack
Pragmatic ways of using Rust in your data project
Prompt Engineering 101
PyCon & PyData Berlin 2023: Lightning talks from day 1
PyCon & PyData Berlin 2023: Lightning talks from day 2
Raised by Pandas, striving for more: An opinionated introduction to Polars
Rapid model development and stable, high-performance deployments
Shrinking gigabyte sized scikit-learn models for deployment
Teaching Neural Networks a Sense of Geometry
The Battle of Giants - Causality vs NLP - From Theory to Practice
The Beauty of Zarr
The bumps in the road - A retrospective on my data visualisation mistakes
The future of the Jupyter Notebook interface
The Spark of Big Data - An Introduction to Apache Spark
Towards Learned Database Systems
Unlocking Information - Creating Synthetic Data for Open Access
Use Spark from anywhere - A Spark client in Python powered by Spark Connect
Using transformers – a drama in 512 tokens
Visualizing your computer vision data is not a luxury, it's a necessity
WALD - A Modern & Sustainable Analytics Stack
When A/B testing isn't an option - an introduction to quasi-experimental methods
'Who is an NLP expert?' - Lessons from building an in-house QA-system
Why GPU Clusters Don't Need to Go Brrr?
Writing Plugin Friendly Python Applications