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https://github.com/lacerbi/ibl-2020-tutorial

Tutorial on computational modeling and statistical model fitting part of the IBL Computational Neuroscience course (2020).
https://github.com/lacerbi/ibl-2020-tutorial

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Tutorial on computational modeling and statistical model fitting part of the IBL Computational Neuroscience course (2020).

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# IBL tutorial on computational modeling and statistical model fitting

This tutorial is part of the internal *IBL Computational Neuroscience Course* organized by the [International Brain Laboratory](https://www.internationalbrainlab.com/) in Spring 2020.
The tutorial instructor for this part of the course is [Luigi Acerbi](http://luigiacerbi.com/).

## Tutorial instructions

- Clone or fork this GitHub repository, or [download](https://github.com/lacerbi/ibl-2020-tutorial/archive/master.zip) and unzip the tutorial folder somewhere on your computer.
- To run the tutorial, you will need a standard scientific Python 3.x installation with Jupyter notebook (such as [Anaconda](https://www.anaconda.com/distribution/)).
- You will also need the `CMA-ES` optimization algorithm (see [here](https://github.com/CMA-ES/pycma)). You can install CMA-ES from the command line with `pip install cma`.
- Then open the Jupyter notebook `ibl-intro-model-fitting-notebook.ipynb` (you should have *Jupyter notebook* installed as part of Anaconda).

## Additional materials

- Slides of the lectures are available [here](https://github.com/lacerbi/ibl-2020-tutorial/blob/master/acerbi-ibl-compneuro-apr2020-slides.pdf).
- For any additional question, please email the course instructor at luigi.acerbi@internationalbrainlab.org.

## License

Code and scripts in this repository are released under the terms of the [MIT License](https://github.com/lacerbi/ibl-2020-tutorial/blob/master/LICENSE).