This material is designed to provide an introduction to the basic tools used in the Van Valen Lab, including Unix, Git, and Docker. There are also interactive Jupyter notebooks introducting Python and its scientific computing environment (NumPy, SciPy, and scikit-image) as well as common deep learning libraries like TensorFlow and Keras.
Please start with the introductory docs for common software development tools.
When ready, clone this repository and run the Jupyter notebooks locally.
- Basic Python, Numpy, and Scipy exercises
- Intro to Python image processing for live cell imaging
- Intro to deep learning with tensorflow
These notebooks and tutorials build on and include material from earlier work:
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The basic Python tutorial (including numpy, matplotlib, and some of the file handling) comes largely from work by Volodymyr Kuleshov and Isaac Caswell on the CS231n Python tutorial by Justin Johnson.
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The flow statements and SciPy sections in Day 1 come largely from work by Rajath Kumar. Those original notes, in turn, were updated for Python 3 and amended for use in Monash University mathematics courses by Andreas Ernst.
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The image processing tutorials come largely from Jonas Hartmann's (Gilmour group, EMBL Heidelberg) Python BioImage Analysis Tutorial.