Version 0.10 Aug. 27, 2019

We had to move some sessions, so if you were planning on seeing them, check their new dates or locations:

• “Introduction to SciPy” by Gert-Ludwig Ingold (Sept. 3, 2019, 9 a.m. → Sept. 3, 2019, 11 a.m.)
• “A Tour of the Data Visualization Ecosystem of Python” by Giovanni De Gasperis (Sept. 3, 2019, 11 a.m. → Sept. 3, 2019, 9 a.m.)

Version 0.9 Aug. 27, 2019

We have new sessions!

• “Deep Learning without a PhD”
• “Debugging in JupyterLab”

Sadly, we had to cancel sessions:

• “Get Started with Variational Inference using Python” by Suriyadeepan Ramamoorthy
• “Environmental Research and Citizen Science using fractaL” by Saulo Jacques

Version 0.8 Aug. 14, 2019

We have a new session: “3D image processing with scikit-image” by Alexandre de Siqueira .

We sadly had to cancel a session: “Introduction to TensorFlow 2.0” by Brad Miro.

Version 0.7 Aug. 4, 2019

We have a new session: “How a voice assistant works” by Miren Urteaga Aldalur .

Version 0.6 July 26, 2019

We have a new session: “Data sciences in a polyglot world with xtensor and xframe” by Sylvain Corlay, Wolf Vollprecht .

We have moved a session around: “A practical guide towards algorithmic bias and explainability in machine learning” by Alejandro Saucedo (Sept. 5, 2019, noon, Track 2 (Baroja) → Sept. 5, 2019, 2:45 p.m., Track 1 (Mitxelena)).

Version 0.5 July 26, 2019

We have a new session: “Astronomical Image Processing” by Samuel FARRENS .

We had to move some sessions, so if you were planning on seeing them, check their new dates or locations:

• “Effectively using matplotlib” by Tim Hoffmann (Track 2 (Baroja) → Track 3 (Oteiza))
• “A Tour of the Data Visualization Ecosystem of Python” by Giovanni De Gasperis (Sept. 2, 2019, 4 p.m. → Sept. 3, 2019, 11 a.m.)

Version 0.4 July 25, 2019

We have new sessions!

• “HPC and Python: Intel’s work in enabling the scientific computing community”
• “In the Shadow of the Black Hole”
• “Introduction to pandas”
• “From Galaxies to Brains! - Image processing with Python”
• “Introduction to SciPy”

We sadly had to cancel a session: “PyTorch is not only for deep learning!” by Alexey Sizanov.

Version 0.3 July 3, 2019

We had to move some sessions, so if you were planning on seeing them, check their new dates or locations:

• “Dashboarding with Jupyter notebooks, voila and widgets” by Maarten Breddels, Martin Renou (Sept. 4, 2019, 4:05 p.m., Track 2 (Baroja) → Sept. 4, 2019, 3:15 p.m., Track 3 (Oteiza))
• “QuTiP: the quantum toolbox in Python as an ecosystem for quantum physics exploration and quantum information science” by Nathan Shammah, Alexander Pitchford (Sept. 4, 2019, 4:05 p.m., Track 3 (Oteiza) → Sept. 4, 2019, noon, Track 2 (Baroja))
• “Modern Data Science: A new approach to DataFrames and pipelines” by Jovan Veljanoski, Maarten Breddels (Sept. 4, 2019, 2:40 p.m. → Sept. 4, 2019, noon)
• “ToFu - an open-source python/cython library for synthetic tomography diagnostics on Tokamaks” by Didier VEZINET, Laura Mendoza (Sept. 4, 2019, 2:05 p.m. → Sept. 4, 2019, 3:15 p.m.)
• “Scientific DevOps: Designing Reproducible Data Analysis Pipelines with Containerized Workflow Managers” by Nicholas Del Grosso (Sept. 4, 2019, 11:40 a.m. → Sept. 4, 2019, 2:45 p.m.)
• “Exceeding Classical: Probabilistic Data Structures in Data Intensive Applications” by Andrii Gakhov (Sept. 5, 2019, 11:40 a.m., Track 1 (Mitxelena) → Sept. 5, 2019, 11 a.m., Track 3 (Oteiza))
• “High performance machine learning with dislib” by Javier Álvarez (Sept. 5, 2019, 2 p.m. → Sept. 5, 2019, 3:45 p.m.)
• “Best Coding Practices in Jupyterlab” by Alexander CS Hendorf (Sept. 4, 2019, 3:40 p.m., Track 2 (Baroja) → Sept. 4, 2019, 4:30 p.m., Track 1 (Mitxelena))
• “A practical guide towards algorithmic bias and explainability in machine learning” by Alejandro Saucedo (Sept. 5, 2019, 3:30 p.m. → Sept. 5, 2019, noon)
• “Caterva: A Compressed And Multidimensional Container For Big Data” by Francesc Alted (Sept. 4, 2019, 2:05 p.m. → Sept. 4, 2019, 3:15 p.m.)
• “TelApy a Python module to compute free surface flows and sediments transport in geosciences” by yoann audouin (Sept. 5, 2019, 3:30 p.m. → Sept. 5, 2019, 4:45 p.m.)
• “Lessons learned from comparing Numba-CUDA and C-CUDA” by Lena Oden (Sept. 5, 2019, 11:45 a.m., Track 2 (Baroja) → Sept. 4, 2019, 4:45 p.m., Track 1 (Mitxelena))
• “High Voltage Lab Common Code Basis library: a uniform user-friendly object-oriented API for a high voltage engineering research.” by Mikołaj Rybiński (Sept. 5, 2019, 11:05 a.m. → Sept. 4, 2019, 4:45 p.m.)
• “PSYDAC: a parallel finite element solver with automatic code generation” by Yaman Güçlü (Sept. 5, 2019, 12:05 p.m. → Sept. 5, 2019, 4:45 p.m.)
• “Understanding Numba” by Valentin Haenel (Sept. 4, 2019, 3:30 p.m., Track 1 (Mitxelena) → Sept. 5, 2019, 2:45 p.m., Track 2 (Baroja))
• “PyPy meets SciPy” by Ronan Lamy (Sept. 4, 2019, 4:05 p.m., Track 1 (Mitxelena) → Sept. 5, 2019, 3:15 p.m., Track 2 (Baroja))
• “Environmental Research and Citizen Science using fractaL” by Saulo Jacques (Sept. 5, 2019, 3:50 p.m., Track 3 (Oteiza) → Sept. 4, 2019, 3:45 p.m., Track 2 (Baroja))
• “Driving a 30m Radio Telescope with Python” by Francesco Pierfederici (Sept. 4, 2019, 3:30 p.m. → Sept. 5, 2019, 11:30 a.m.)
• “Introduction to TensorFlow 2.0” by Brad Miro (Sept. 5, 2019, 10:30 a.m. → Sept. 5, 2019, 11 a.m.)
• “Constrained Data Synthesis” by Nick Radcliffe (Sept. 4, 2019, 10:30 a.m. → Sept. 4, 2019, 2:45 p.m.)
• “PyFETI - An easy and massively Dual Domain Decomposition Solver for Python” by Guilherme Jenovencio (Sept. 5, 2019, 2:20 p.m., Track 2 (Baroja) → Sept. 4, 2019, 4:30 p.m., Track 3 (Oteiza))
• “The Rapid Analytics and Model Prototyping (RAMP) framework: tools for collaborative data science challenges” by Guillaume Lemaitre, Joris Van den Bossche (Sept. 5, 2019, 11:05 a.m. → Sept. 4, 2019, 4:45 p.m.)
• “Inside NumPy: preparing for the next decade” by Matti Picus (Sept. 4, 2019, 10:30 a.m. → Sept. 5, 2019, 10:30 a.m.)
• “Modin: Scaling the Capabilities of the Data Scientist, not the machine” by Devin Petersohn, Devin Petersohn (Sept. 4, 2019, 11:05 a.m. → Sept. 4, 2019, 3:45 p.m.)
• “What about tests in Machine Learning projects?” by Sarah Diot-Girard (Sept. 4, 2019, 11:05 a.m. → Sept. 4, 2019, noon)
• “Recent advances in python parallel computing” by Pierre Glaser (Sept. 4, 2019, 12:15 p.m., Track 1 (Mitxelena) → Sept. 5, 2019, 11:30 a.m., Track 2 (Baroja))
• “Can we make Python fast without sacrificing readability? numba for Astrodynamics” by Juan Luis Cano Rodríguez (Sept. 4, 2019, 1:45 p.m., Track 3 (Oteiza) → Sept. 5, 2019, 4:30 p.m., Track 2 (Baroja))
• “Apache Arrow: a cross-language development platform for in-memory data” by Joris Van den Bossche (Sept. 4, 2019, 1:30 p.m. → Sept. 4, 2019, 2:45 p.m.)
• “Sufficiently Advanced Testing with Hypothesis” by Zac Hatfield-Dodds (Sept. 4, 2019, 10:30 a.m. → Sept. 4, 2019, 11:30 a.m.)
• “How to process hyperspectral data from a prototype imager using Python” by Matti Eskelinen (Sept. 4, 2019, 1:30 p.m., Track 2 (Baroja) → Sept. 5, 2019, 4:30 p.m., Track 1 (Mitxelena))
• “emzed: a Python based framework for analysis of mass-spectrometry data” by Uwe Schmitt (Sept. 4, 2019, 2:40 p.m., Track 2 (Baroja) → Sept. 5, 2019, 3:15 p.m., Track 3 (Oteiza))
• “The Magic of Neural Embeddings with TensorFlow 2” by Oliver Zeigermann (Sept. 5, 2019, 2 p.m. → Sept. 5, 2019, 11:30 a.m.)
• “Distributed GPU Computing with Dask” by Peter Andreas Entschev (Sept. 4, 2019, 11:40 a.m. → Sept. 4, 2019, 11:30 a.m.)
• “Histogram-based Gradient Boosting in scikit-learn 0.21” by Olivier Grisel (Sept. 5, 2019, 10:30 a.m. → Sept. 5, 2019, 11 a.m.)
• “High quality video experience using deep neural networks” by Marco Bertini, Tiberio Uricchio (Sept. 5, 2019, 2:35 p.m. → Sept. 5, 2019, noon)
• “vtext: fast text processing in Python using Rust” by Roman Yurchak (Sept. 5, 2019, 3:30 p.m., Track 1 (Mitxelena) → Sept. 5, 2019, 3:45 p.m., Track 3 (Oteiza))
• “Tracking migration flows with geolocated Twitter data” by Antònia Tugores (Sept. 5, 2019, 2 p.m., Track 3 (Oteiza) → Sept. 5, 2019, 3:15 p.m., Track 1 (Mitxelena))
• “pystencils: Speeding up stencil computations on CPUs and GPUs” by Martin Bauer (Sept. 5, 2019, 11:25 a.m., Track 2 (Baroja) → Sept. 5, 2019, 4:30 p.m., Track 3 (Oteiza))
• “Make your Python code fly at transonic speeds!” by Pierre Augier (Sept. 5, 2019, 2:40 p.m., Track 2 (Baroja) → Sept. 4, 2019, 3:45 p.m., Track 3 (Oteiza))
• “Visual Diagnostics at Scale” by Dr. Rebecca Bilbro (Sept. 4, 2019, 11:25 a.m. → Sept. 5, 2019, 10:30 a.m.)
• “VeloxChem: Python meets quantum chemistry and HPC” by Olav Vahtras (Sept. 5, 2019, 10:30 a.m. → Sept. 5, 2019, 2:45 p.m.)
• “Controlling a confounding effect in predictive analysis.” by Darya Chyzhyk (Sept. 4, 2019, 11:05 a.m. → Sept. 4, 2019, 4:30 p.m.)
• “Enhancing & re-designing the QGIS user interface – a deep dive” by Sebastian M. Ernst (Sept. 5, 2019, 2:35 p.m., Track 3 (Oteiza) → Sept. 5, 2019, 4:45 p.m., Track 1 (Mitxelena))
• “Deep Learning for Understanding Human Multi-modal Behavior” by Ricardo Manhães Savii (Sept. 5, 2019, 12:15 p.m. → Sept. 5, 2019, 3:45 p.m.)
• “Get Started with Variational Inference using Python” by Suriyadeepan Ramamoorthy (Sept. 4, 2019, 2:05 p.m. → Sept. 5, 2019, 10:30 a.m.)
• “Matrix calculus with SymPy” by Francesco Bonazzi (Sept. 4, 2019, 2:40 p.m. → Sept. 5, 2019, noon)
• “PyTorch is not only for deep learning!” by Alexey Sizanov (Sept. 5, 2019, 11:05 a.m. → Sept. 5, 2019, 2:45 p.m.)

Version 0.2 July 3, 2019

We have new sessions!

• “Effectively using matplotlib”
• “Never get in a battle of bits without ammunition”
• “MNE-Python, a toolkit for neurophysiological data”
• “Get Started with Variational Inference using Python”
• “A Tour of the Data Visualization Ecosystem of Python”
• “Deep Diving into GANs: From Theory to Production with TensorFlow 2.0”
• “Caterva: A Compressed And Multidimensional Container For Big Data”
• “Performing Quantum Measurements in QuTiP”
• “Histogram-based Gradient Boosting in scikit-learn 0.21”
• “Introduction to scikit-learn: from model fitting to model interpretation”
• “Make your Python code fly at transonic speeds!”
• “Lessons learned from comparing Numba-CUDA and C-CUDA”
• “scikit-fdiff, a new tool for PDE solving”
• “Introduction to TensorFlow 2.0”
• “PyFETI - An easy and massively Dual Domain Decomposition Solver for Python”
• “Deep Learning for Understanding Human Multi-modal Behavior”
• “Recent advances in python parallel computing”
• “How to process hyperspectral data from a prototype imager using Python”
• “Modin: Scaling the Capabilities of the Data Scientist, not the machine”

We sadly had to cancel a session: “Breaking pandas” by Marc Garcia.

We had to move some sessions, so if you were planning on seeing them, check their new dates or locations:

• “PhonoLAMMPS: Phonopy with LAMMPS made easy” by Abel Carreras (Sept. 4, 2019, 4:40 p.m. → Sept. 4, 2019, 11:40 a.m.)
• “CFFI, Ctypes, Cython, Cppyy: how to run C code from Python” by Matti Picus (Track 2 (Baroja) → Track 3 (Oteiza))
• “kESI - a kernel-based method for reconstruction of sources of brain electric activity in realistic brain geometries” by Marta Kowalska, Jakub M. Dzik (Sept. 4, 2019, 4:40 p.m. → Sept. 4, 2019, 2:50 p.m.)
• “From Modeler to Programmer” by Mike Müller (Sept. 4, 2019, 4:40 p.m. → Sept. 4, 2019, 4:25 p.m.)
• “Parallelizing Python applications with PyCOMPSs” by Javier Conejero (Track 3 (Oteiza) → Track4 (Chillida))
• “Speed up your python code” by Jérémie du Boisberranger (Sept. 3, 2019, 4 p.m., Track 2 (Baroja) → Sept. 2, 2019, 4 p.m., Track 3 (Oteiza))
• “kCSD - a Python package for reconstruction of brain activity” by Marta Kowalska, Jakub M. Dzik (Sept. 2, 2019, 4 p.m. → Sept. 3, 2019, 4 p.m.)
• “Really reproducible behavioural paper” by Jakub M. Dzik (Sept. 4, 2019, 4:40 p.m. → Sept. 4, 2019, 1:15 p.m.)

Version 0.1 July 1, 2019

We released our first schedule!