Abel Carreras

“PhonoLAMMPS: Phonopy with LAMMPS made easy”


Alejandro Saucedo

“A practical guide towards algorithmic bias and explainability in machine learning”


Alexander CS Hendorf

“Best Coding Practices in Jupyterlab”


Alexander Pitchford

“QuTiP: the quantum toolbox in Python as an ecosystem for quantum physics exploration and quantum information science”


Alexandre de Siqueira

“3D image processing with scikit-image”


Andrii Gakhov

“Exceeding Classical: Probabilistic Data Structures in Data Intensive Applications”


Antònia Tugores

“Tracking migration flows with geolocated Twitter data”


Chandrasekhar Ramakrishnan

“Reproducible Data Science in Python”


Darya Chyzhyk

“Controlling a confounding effect in predictive analysis.”


David Liu

“HPC and Python: Intel’s work in enabling the scientific computing community”


Devin Petersohn

“Modin: Scaling the Capabilities of the Data Scientist, not the machine”


Devin Petersohn

“Modin: Scaling the Capabilities of the Data Scientist, not the machine”


Didier VEZINET

“ToFu - an open-source python/cython library for synthetic tomography diagnostics on Tokamaks”


Dr. Mike Müller

“From Modeler to Programmer”


Dr. Rebecca Bilbro

“Visual Diagnostics at Scale”


Dr. Tania Allard

“Building data pipelines in Python: Airflow vs scripts soup”


Emanuele Ghelfi

“Deep Diving into GANs: From Theory to Production with TensorFlow 2.0”


Federico Di Mattia

“Deep Diving into GANs: From Theory to Production with TensorFlow 2.0”


Francesc Alted

“Caterva: A Compressed And Multidimensional Container For Big Data”


Francesco Bonazzi

“Matrix calculus with SymPy”


Francesco Pierfederici

“Driving a 30m Radio Telescope with Python”


Gert-Ludwig Ingold

“Introduction to SciPy”


Giovanni De Gasperis

“A Tour of the Data Visualization Ecosystem of Python”


Guilherme Jenovencio

“PyFETI - An easy and massively Dual Domain Decomposition Solver for Python”


Guillaume Lemaitre

“The Rapid Analytics and Model Prototyping (RAMP) framework: tools for collaborative data science challenges” | “Introduction to scikit-learn: from model fitting to model interpretation”


Jakub M. Dzik

“kCSD - a Python package for reconstruction of brain activity” | “Really reproducible behavioural paper” | “kESI - a kernel-based method for reconstruction of sources of brain electric activity in realistic brain geometries”


Javier Álvarez

“High performance machine learning with dislib”


Javier Conejero

“Parallelizing Python applications with PyCOMPSs”


Jérémie du Boisberranger

“Speed up your python code”


Jeremy Tuloup

“Debugging in JupyterLab”


Joan Massich

“MNE-Python, a toolkit for neurophysiological data”


Joris Van den Bossche

“The Rapid Analytics and Model Prototyping (RAMP) framework: tools for collaborative data science challenges” | “Introduction to geospatial data analysis with GeoPandas and the PyData stack” | “Apache Arrow: a cross-language development platform for in-memory data”


Josh Gordon

“Hands-on TensorFlow 2.0”


Jovan Veljanoski

“Modern Data Science: A new approach to DataFrames and pipelines”


Juan Luis Cano Rodríguez

“Can we make Python fast without sacrificing readability? numba for Astrodynamics”


Laura Mendoza

“ToFu - an open-source python/cython library for synthetic tomography diagnostics on Tokamaks”


Lena Oden

“Lessons learned from comparing Numba-CUDA and C-CUDA”


Maarten Breddels

“Modern Data Science: A new approach to DataFrames and pipelines” | “Dashboarding with Jupyter notebooks, voila and widgets”


Marc Garcia

“Introduction to pandas”


Marco Bertini

“High quality video experience using deep neural networks”


Marta Kowalska

“kCSD - a Python package for reconstruction of brain activity” | “kESI - a kernel-based method for reconstruction of sources of brain electric activity in realistic brain geometries”


Martin Bauer

“pystencils: Speeding up stencil computations on CPUs and GPUs”


Martin Renou

“Dashboarding with Jupyter notebooks, voila and widgets”


Matti Eskelinen

“How to process hyperspectral data from a prototype imager using Python”


Matti Picus

“Inside NumPy: preparing for the next decade” | “CFFI, Ctypes, Cython, Cppyy: how to run C code from Python”


Michele "Ubik" De Simoni

“Deep Diving into GANs: From Theory to Production with TensorFlow 2.0”


Mike Müller

“Getting Started with JupyterLab”


Mikołaj Rybiński

“High Voltage Lab Common Code Basis library: a uniform user-friendly object-oriented API for a high voltage engineering research.”


Miren Urteaga Aldalur

“How a voice assistant works”


Nathan Shammah

“QuTiP: the quantum toolbox in Python as an ecosystem for quantum physics exploration and quantum information science”


Nicholas Del Grosso

“Scientific DevOps: Designing Reproducible Data Analysis Pipelines with Containerized Workflow Managers”


Nick Radcliffe

“Constrained Data Synthesis”


Nicolas Cellier

“scikit-fdiff, a new tool for PDE solving”


Olav Vahtras

“VeloxChem: Python meets quantum chemistry and HPC”


Oliver Zeigermann

“The Magic of Neural Embeddings with TensorFlow 2”


Olivier Grisel

“Histogram-based Gradient Boosting in scikit-learn 0.21” | “Introduction to scikit-learn: from model fitting to model interpretation”


Paige Bailey

“Deep Learning without a PhD”


Paolo Galeone

“Deep Diving into GANs: From Theory to Production with TensorFlow 2.0”


Peter Andreas Entschev

“Distributed GPU Computing with Dask”


Pierre Augier

“Make your Python code fly at transonic speeds!”


Pierre Glaser

“Recent advances in python parallel computing”


Ricardo Manhães Savii

“Deep Learning for Understanding Human Multi-modal Behavior”


Rok Roškar

“Reproducible Data Science in Python”


Roman Yurchak

“vtext: fast text processing in Python using Rust”


Ronan Lamy

“PyPy meets SciPy”


Samuel FARRENS

“Astronomical Image Processing” | “From Galaxies to Brains! - Image processing with Python”


Sarah Diot-Girard

“What about tests in Machine Learning projects?”


Sara Issaoun

“In the Shadow of the Black Hole”


Sebastian M. Ernst

“Enhancing & re-designing the QGIS user interface – a deep dive”


Simon Cross

“Performing Quantum Measurements in QuTiP”


Sylvain Corlay

“Data sciences in a polyglot world with xtensor and xframe”


Tiberio Uricchio

“High quality video experience using deep neural networks”


Tim Hoffmann

“Effectively using matplotlib”


Uwe Schmitt

“emzed: a Python based framework for analysis of mass-spectrometry data”


Valentin Haenel

“Understanding Numba” | “Create CUDA kernels from Python using Numba and CuPy.”


Valerio Maggio

“Never get in a battle of bits without ammunition”


Wolf Vollprecht

“Data sciences in a polyglot world with xtensor and xframe”


Yaman Güçlü

“PSYDAC: a parallel finite element solver with automatic code generation”


yoann audouin

“TelApy a Python module to compute free surface flows and sediments transport in geosciences”


Zac Hatfield-Dodds

“Sufficiently Advanced Testing with Hypothesis” | “Sufficiently Advanced Testing with Hypothesis”