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Posters
Meet Runpandas: How Applied Data Science with Python helped me to run better!
Marcel Caraciolo
causal-curve: tools to perform causal inference given a continuous treatment
Roni Kobrosly
Analyzing YouTube using Python and Machine Learning
Jyotika Singh
Efficient Active Machine Learning for Crowdsourcing
Scott Sievert
Training machine learning models faster with Dask
Joe Holt and Scott Sievert
PyStar: Realtime Augmented Reality data visualizationusing Python and iOS.
Mauricio Hernandes
Build Your First Cyber Forensic Application using Python
Gajendra Deshpande
Jostar: A Feature Selection Library for Data Sciences in Python
Amirhossein Hassanzadeh and Jan van Aardt
Analysis and Verification of Mixed-mode Signal Chains for Analog Signal Acquisition using Python
Mark Thoren
Cell Tracking in 3D using deep learning segmentations
Varun Kapoor and Claudia Carabana Garcia
Leveraging the power of Python to accelerate GPU computing in multiple industries
Joongi Kim, Eunjin Hwang, Sergey Leksikov and Jeongkyu Shin
IPySpaghetti: A dataflow interactive environment in Jupyter Lab
Corentin Cadiou
Microwave Image Processing: Exploring SAR images from Foundations to Frontiers through Python
Shubham Sharma
Data Processing on Ray
Sangbin Cho
Weaviate Vector Search Engine - Introduction
Laura Ham
Multilingual Natural Language Processing using Python
Gajendra Deshpande
Inventing Curriculum using Python and spaCy
Gajendra Deshpande
A Gentle Introduction to Causal Inference
Eyal Kazin
A Gentle Introduction To Multi-Objective Optimisation
Eyal Kazin
Using the scientific Python stack to analyze Low Energy Electron Microscopy data
Tobias A. de Jong, David N. L. Kok, Johannes Jobst, Tjerk Benschop and Sense Jan van der Molen
Persistent BinderHub: The best of both worlds
Mridul Seth and Arnim Bleier
Mitigating Cognitive Bias in Software Artifacts
Matthew Widjaja, Amanda Kraft, Trevor Sands and Brad Galego
Distributed XGBoost on Ray
Kai Fricke
Figpager: Multipage graphics with matplotlib
Eben Pendleton
How to Speed Up Scikit-Learn Model Training
Michael Galarnyk
mlf-core enables GPU deterministic machine learning
Lukas Heumos, Philipp Ehmele and Edmund Miller
Use Case: How PDFrw and fillable forms improves throughput at a Covid-19 Vaccine Clinic
Haw-Minn Lu and Jose Unpingco
Fire-and-forget distributed function execution with funcX
Ryan Chard, Yadu Babuji, Zhuozhao Li, Yongyan Rao, Josh Bryan, Tyler Skluzacek, Ben Galewsky, Daniel S. Katz, Ian Foster and Kyle Chard
Breaking down the Jupyter notebook monolith: Building reliable notebook-based pipelines with Ploomber
Eduardo Blancas Reyes
Declair: a hyperparameter search configuration framework
Krzysztof Cybulski, Tim De Jong and Marco Puts
CLAIMED, a visual and scalable component library for Trusted AI
Romeo Kienzler and Ivan Nesic
sktime - a Unified Framework for Machine Learning with Time Series
Markus L�ning
Caterva: A Compressed And Multidimensional Container For Medium/Big Data
Francesc Alted, Aleix Alcacer and Christian Steiner
Segmentation of tumors in brain: U-Nets and FPNs
Sourodip Ghosh
pycid: A Python Library for Causal Influence Diagrams
James Fox, Tom Everitt and Ryan Carey
On the Daskening of yt
Chris Havlin, Kacper Kowalik, Madicken Munk and Matthew Turk
Creating Learner Personas to Teach Data Science Effectively
Daniel Chen
Interpretable Machine Learning with PySR, a new High-Performance Symbolic Regression Package
Miles Cranmer
Adaptation in modern Markov chain Monte Carlo
Colin Carroll
Classification of Diffuse Subcellular Morphologies
Neelima Pulagam, Marcus Hill, Mojtaba Fazli, Meekail Zain, Rachel Mattson, Andrew Durden, Frederick Quinn, Chakra Chennubhotla and Shannon Quinn
Modernizing computing by structural biologists with Jupyter and Colab
Blaine Mooers
Performance of ulab - a NumPy/SciPy-like MicroPython module for microcontrollers
Pedro H. R. da S. Camara, Roberto Colistete Jr, Thiago F. Santos and Eduardo D. Stefanato
Scientific MicroPython on Microcontrollers
Roberto Colistete Jr
Bayesian Tools for Observational Cosmology of Type Ia Supernovae (BETOC-S) using Numba and CuPy
Roberto Colistete Jr
Create and Explore Data Pipelines with Elyra and JupyterLab
Alan Chin