PyData & Scientific Libraries Stack
11 talks from the 2022 edition.
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(Serious) Time for Time Series ▶ Recording 📝 Transcript
Marysia Winkels, James Hayward
From inventory to website visitors, resource planning to financial data, time-series data is all around us. Knowing what comes next is key to success in this dynamically changing world. And for that we need reliable...
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5 Steps to Speed Up Your Data-Analysis on a Single Core ▶ Recording 📝 Transcript
Jonathan Striebel
Your data analysis pipeline works. *Nice.* Could it be faster? *Probably.* Do you need to parallelize? *Not yet.* We'll go through optimization steps that **boost the performance of your data analysis pipeline on a...
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Creating 3D Maps using Python ▶ Recording 📝 Transcript
Martin Christen
In this talk it is shown how to create 3D Maps using Open Data and Python. There are many open data sources available now for direct download, for example on AWS ( https://aws.amazon.com/opendata ). This talks shows...
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Data Apis: Standardization of N-dimensional arrays and dataframes ▶ Recording 📝 Transcript
Stephannie Jimenez Gacha
We would like to introduce the consortium of Data APIs, where we will be presenting our motivation, objectives and progress of the standardization process after one year of activity. We will dive into a small history...
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Data Science at Scale with Dask ▶ Recording 📝 Transcript
Richard Pelgrim
A Pythonic introduction to methods for scaling your data science and machine learning work to larger datasets and larger models with Dask, all while staying within the comfort of the tools and APIs you know and love...
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Easy and flexible imaging with the Core Imaging Library
Vaggelis Papoutsellis, Dr. Jakob Sauer Jørgensen
In this talk, we present the [Core Imaging Library (CIL)](https://github.com/TomographicImaging/CIL), an open-source, object-oriented Python library for solving large scale imaging inverse problems. We give a brief...
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Flexible ML Experiment Tracking System for Python Coders with DVC and Streamlit ▶ Recording 📝 Transcript
Antoine Toubhans
There are tons of tools to do data science. Too often, data scientists end up using a monolithic AI platform that “does everything by clicking on a UI”. In this talk, I will walk you through a pythonic and flexible...
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Introducing the Dask Active Memory Manager ▶ Recording 📝 Transcript
Guido Imperiale
The 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.
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On Blocks, Copies and Views: updating pandas' internals ▶ Recording 📝 Transcript
Joris Van den Bossche
a.k.a. “Getting rid of the SettingWithCopyWarning” Pandas’ current behavior on whether indexing returns a view or copy is confusing, even for experienced users. But it doesn’t have to be this way. We can make this...
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Reproducible machine learning and science with python ▶ Recording 📝 Transcript
Prabhant Singh
With machine learning being used in all domains of science, reproducibility and openness is major concern for these experiments and workflows, This tutorial will discuss various experiment tracking tools and focus on...
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sktime - python toolbox for time series: advanced forecasting - probabilistic, global and hierarchical
Franz Kiraly
sktime is a widely used scikit-learn compatible library for learning with time series. The forecasting module of sktime provides a unified, sklearn-compatible, and composable interface to the pydata/numfocus...