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Slides from the 17th Python in Science Conferences (SciPy)
I am someone who is trying to submit some slides
That's because you are a amazing! Here's how it works:
- You'll need a GitHub account. You can sign up here.
- Fork this repository by clicking the "fork" button.
- Add your slide deck to the local (on your laptop) copy of the repository. To make it easy for people to find, we prefer that it be inside a directory that is a simpified version of the name of your paper. You can add other files too, if you like.
- Add a link to it in the README file (please try to keep it alphabetical). The markdown syntax looks like this:
[Name of Paper - Name of Presenter](https://https://github.com/deniederhut/Slides-SciPyConf-2018/blob/master/url-to-your-folder)
- Commit your changes:
git commit -am "Submitting my slides!"
. - Push the changes to your fork:
git push origin master
- Open a PR to dniederhut/master (click the "open a pull request button")
- Celebrate!
I am someone who is trying to find a slide deck
That's because you are awesome! See the list below:
- Addressing Multithreading and Multiprocessing in Transparent and Pythonic Methods - David Liu and Anton Malakhov [Repo | Slides]
- Apache Arrow: A Cross-Language Development Platform for In-memory Data - Wes McKinney
- Binder 2.0: The Next Generation of Reproducible Scientific Environments with repo2docker and BinderHub - Chris Holdgraf and Min Ragan-Kelley
- Bringing ipywidgets Support to plotly.py - Jon Mease
- Building an object-oriented Python interface for the Generic Mapping Tools - Leonardo Uieda [Repo | Notebook]
- cis_interface: A Python package for connecting scientific models across scales and languages - Meagan Lang [Repo | Docs]
- Cloudknot: A Python library to run your existing code on AWS Batch - Adam Richie-Halford [Repo | Slides]
- Convex Optimization in Python with CVXPY
- Data Visualization for Scientists - Zan Armstrong
- dask-ml: scalable machine learning
- Detecting anomalies using statistical distances - Charles Masson
- Development of MetPy’s Declarative Plotting Interface
- Devops Empowered Data Science with Ansible - Tim Hopper
- Harnessing the Power of Scientific Python to Investigate the Biogeochemistry of the South Pacific - Noelle Held and Jaclyn Saunders
- Econ-ARK and HARK: Open Source Tools for Computational Economics - Matthew N. White
- ITK: The Insight Segmentation and Registration Toolkit - Matthew McCormick
- Jupyter Notebook Driven Development with PYNT (PYthon iNTeractive) - Edward Banner [Repo] [Slides]
- Learning mechanical vibrations through computation thinking - Jason Moore, Kenneth Lyons
- Pangeo: A Big-data Ecosystem for Scalable Earth System Science - Joe Hamman
- Parsl: Enabling Scalable Interactive Computing in Python - Kyle Chard
- Safe Handling Instructions for Missing Data - Dillon Niederhut
- Scalable Computer Vision with Aerial and Satellite Imagery - Virginia Ng
- scikit-build: A Build System Generator for CPython C/C++/Fortran/Cython Extensions - Jean-Christophe Fillion-Robin
- "Resurrecting Ancient Proteins in Python" slides - Zach Sailer [Repo | Notebook]
- SatPy - A Python Library for Weather Satellite Imagery - David Hoese
- Should this Drug be Approved? A Bayesian’s Answer with Stan - Konstantinos Vamvourellis & Marianne Corvellec
- Sneaking Data into Containers with the Whole Tale - Kacper Kowalik
- UMAP: Uniform Manifold Approximation and Projection for Dimension Reduction - Leland McInnes
- Website for interacting with oceanographic data and numerical model output - Kristen Thyng
- Yaksh: Facilitating Learning by Doing - Prabhu Ramachandran
- "Leveraging Jupyter, Rust, and WebAssembly for Browser-Based Visual Data Exploration" slides - Madicken Munk [Repo | Notebook]
- Recipe2Vec or How Does My Robot Know Which Recipes are Related - Meghan Heintz
Lightning talks
- Introducing JOSE: The Journal of Open Source Education - Kyle Niemeyer
- Slicer, Python, Xeus and Jupyter - Jean-Christophe Fillion-Robin
Posters
- itk-jupyter-widgets: Interactive 2D and 3D Image Visualization for Jupyter - Matthew McCormick et. al.
- PyKED: a Python-based tool supporting data analysis and experimental reproducibility in combustion - Kyle Niemeyer & Bryan Weber
- Oxidizing Python: writing extensions in Rust - Luiz Irber