Tutorial Participant Instructions
Still have questions? Visit the individual tutorial channel on scipy2019.slack.com. (Contact [email protected] if you need an invitation to Slack.)
Monday, July 8 8:00 am-Noon
Intro to Python Programming
Matt Davis
Room 101
These are the setup instructions for the Introduction to Python tutorial at SciPy 2019. Please visit https://github.com/jiffyclub/scipy-2019-intro-to-python for up-to-date information on the tutorial.
If you don't already have Anaconda installed, download and install Anaconda for Python 3 (not Python 2): https://www.anaconda.com/distribution/.
If you're prompted to install VS Code we recommend you do install it unless you already have a code editor you prefer.
After installing Anaconda you can test your installation using these instructions: http://docs.anaconda.com/anaconda/user-guide/getting-started/#write-a-python-program-using-anaconda-prompt-or-terminal
Land on Vector Spaces: Practical Linear Algebra with Python
Lorena Barba and Tingyu Wang
Room 201
Tutorial instructions may be viewed at https://github.com/engineersCode/EngComp4_landlinear
Xonsh - Bringing Python Data Science to your Shell
Gil Forsyth and Anthony Scopatz
Room 104
Tutorial materials may be viewed at https://github.com/xonsh/scipy2019_tutorial
Bayesian Statistics Made Simple
Allen Downey
Room 105
Tutorial materials may be viewed at https://allendowney.github.io/BayesMadeSimple/
Modern Time Series Analysis
Aileen Nielsen
Room 203
Python 3.x is required
the following packages should be installed and updated to the most recent version per the sample script:
import tensorflow as tf
import mxnet as mx
import xgboost as xgb
import sklearn
import statsmodels
import numpy as npy
import pandas as pd
Using SatPy to Process Earth-observing Satellite Data
David Hoese
Room 202
Tutorial materials may be viewed at https://github.com/pytroll/tutorial-satpy-half-day
Testing your Python Code with PyTest
John Leeman and Ryan May
Room 106
Tutorial materials may be viewed at https://leemangeophysicalllc.github.io/testing-with-python/
Monday, July 8 1:30 pm-5:30 pm
Bayesian Data Science: Simulation
Hugo Bowne-Anderson and Eric Ma
Room 203
Tutorial materials may be viewed at https://github.com/ericmjl/bayesian-stats-modelling-tutorial.
Complexity Science
Allen Downey
Room 105
Tutorial materials may be viewed at https://allendowney.github.io/ComplexityScience/
Intermediate Methods for Geospatial Data Analysis
Levi Wolf and Serge Rey
Room 202
Tutorial materials may be viewed at https://github.com/pysal/scipy2019-intermediate-gds
Introduction to Numerical Computing with NumPy
Alexandre Chabot-Leclerc
Room 201
Tutorial materials may be viewed at https://github.com/enthought/Numpy-Tutorial-SciPyConf-2019
Lights Camera Action! Scrape, Explore, and Model to Predict Oscar Winners & Box Office Hits
Sebastian Hanus, Deborah Hanus, Patricia Hanus, and Veronica Hanus
Room 104
Tutorial materials may be viewed at https://github.com/oscarpredictor/oscar-predictor
Reproducible Data Science in Python
Chandrasekhar Ramakrishnan and Xu Fei
Room 101
Tutorial materials may be viewed at https://github.com/SwissDataScienceCenter/r10e-ds-py
Visualize any Data Easily, from Notebooks to Dashboards
James Bednar, Jean-Luc Stevens, and Julia Signell
Room 106
Tutorial materials may be viewed at http://holoviz.org
Tuesday, July 9 8:00 am-Noon
Deep Learning Fundamentals: Forward Model, Differentiable Loss Function, and Optimization Routine
Eric Ma
Room 203
Tutorial materials will be available soon
Hands-on Satellite Imagery Analysis
Sara Safavi and Samapriya Roy
Room 101
This tutorial will be using a hosted Jupyter environment. Only a laptop with internet access and a web browser is needed.
Introduction to Bayesian Model Evaluation, Visualization, and Comparison Using Arviz
Ravin Kumar and Colin Carroll
Room 202
Tutorial materials may be viewed at https://github.com/canyon289/bayesian-model-evaluation/
Introduction to Matplotlib
Hannah Aizenman and Thomas Caswell
Room 201
Tutorial materials may be viewed here
RAPIDS: Open GPU Data Science
Anthony Scopatz, Nick Becker, Keith Kraus, Dante Gama Dessavre
Room 106
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Pre-Tutorial Instructions for RAPIDS: Open GPU Data Science
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This tutorial will be conducted via Jupyter Notebooks hosted on cloud service provider machines. Exact URLs for the Jupyter Notebooks will be provided on the day of the tutorial, as they are generated when the cloud machines are spun up.
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Attendees should make sure to use a modern browser, such as a Google Chrome or Mozilla Firefox. Some laptops have security settings that block ports/websockets necessary for accessing cloud-hosted Jupyter Notebooks. To determine whether your laptop has a compatible configuration, please visit https://websocketstest.com . If your results say "WebSockets seem to work for you", you will be able to access the tutorial materials. If WebSockets do not work for you, please consider bringing an alternate laptop or temporarily changing your settings to allow for WebSockets, taking care to comply with any of your IT restrictions if you are using a corporate laptop.
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Attendees will be required to conduct the tutorial on the cloud Notebooks, even if they have CUDA-compatible GPUs in their laptops.
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Simulate and Generate: An Overview to Simulations and Generating Synthetic Data Sets in Python
Aileen Nielsen
Room 105
Python 3.x is required
the following packages should be installed and updated to the most recent version per the sample script:
import numpy as np
import pandas as pd
The Jupyter Interactive Widget Ecosystem
Matt Craig, Jason Grout, Martin Renou, Maarten Breddels, and Sylvain Corlay
Room 104
Tutorial materials may be viewed at https://github.com/jupyter-widgets/tutorial
Tuesday, July 9 1:30 pm-5:30 pm
Escape from Auto-manual Testing with Hypothesis!
Zac Hatfield-Dodds
Room 104
Tutorial materials may be viewed at https://github.com/Zac-HD/escape-from-automanual-testing
Getting Started with JupyterLab
Jason Grout, Matthias Bussonnier, and Stephanie Stattel
Room 202
Tutorial materials may be viewed at https://github.com/jupyterlab/scipy2019-jupyterlab-tutorial#installation
Getting Started with Tensorflow
Josh Gordon and Yufeng Guo
Room 203
Attendees will need a laptop and an internet connection. We will use https://colab.research.google.com for all examples so there is nothing to install in advance.
Image Analysis in Python with SciPy and Scikit-image
Joshua Warner, Juan Nunez-Iglesias, and Stéfan van der Walt
Room 106
Tutorial materials may be viewed at https://github.com/scikit-image/skimage-tutorials/blob/master/preparation.md
Introduction to Data Processing in Python with Pandas
Daniel Chen
Room 201
Tutorial materials may be viewed at https://github.com/chendaniely/scipy-2019-pandas
Multi-dimensional Linked Data Exploration with Glue
Thomas Robitaille
Room 101
Tutorial materials may be viewed at https://github.com/glue-viz/glue/wiki/SciPy-2019-Tutorial-on-Multi-dimensional-Linked-Data-Exploration-with-Glue
Network Analysis Made Simple
Mridul Seth and Eric Ma
Room 105
Tutorial materials may be viewed at https://github.com/ericmjl/Network-Analysis-Made-Simple