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CRN resources

The Center for Reproducible Neuroscience produces a variety of software resources (such as fmriprep and mriqc). In this tutorial, you will learn about some of them.

Cython and numba

Cython is a technology that allows us to easily bridge between python, and the underlying C representations. The main purpose of the library is to take code that is written in python, and, provided some additional amount of (mostly type) information, compile it to C, compile the C code, and bundle the C objects into […]

Docker for scientists

An overview of Docker and other containerization technologies: what containers are, why they’re useful, how to install them, and how to use them. Slides and materials available on GitHub: https://github.com/neurohackweek/docker-for-scientists.

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Introduction to Python

A brief overview of the Python programming language, with an emphasis on tools relevant to data scientists. An interactive Jupyter Notebook (which also doubles as the slides) is available here.

Machine learning with scikit-learn

This session will cover the basics of Scikit-Learn, a popular package containing a collection of tools for machine learning written in Python. See more at http://scikit-learn.org. Outline Main Goal: To introduce the central concepts of machine learning, and how they can be applied in Python using the Scikit-learn Package. Definition of machine learning Data representation in scikit-learn […]

Python packaging

In this tutorial, we will work through setting up a scientific Python package. This will provide an opinionated introduction to some of the ins and outs of Python packaging and package distribution.

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Software testing

An introduction to software testing for scientific code. Materials available here; source code for all materials here.