{"id":17686746,"url":"https://github.com/lacerbi/tics-2020-tutorial","last_synced_at":"2025-04-22T11:49:05.994Z","repository":{"id":97691750,"uuid":"251730756","full_name":"lacerbi/tics-2020-tutorial","owner":"lacerbi","description":"Tutorial on computational modeling and statistical model fitting part of the *Trends in Computational Neuroscience* graduate course of the University of Geneva (2020). 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The course instructor for this part of the course is [Luigi Acerbi](http://luigiacerbi.com/).\n\n## Tutorial instructions\n\n- Download and unzip the tutorial folder somewhere on your computer: [download](https://github.com/lacerbi/tics-2020-tutorial/archive/master.zip).\n- 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/)). \n- 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`.\n- Then open the Jupyter notebook `tics-intro-model-fitting-notebook.ipynb` (you should have *Jupyter notebook* installed as part of Anaconda).\n\n## Additional lecture materials\n\n- Slides of the lectures are available [here](https://github.com/lacerbi/tics-2020-tutorial/blob/master/Acerbi-TICS-2020-slides.pdf).\n- Instructions for the second mini-project related to this part of the course are [here](https://github.com/lacerbi/tics-2020-tutorial/blob/master/TICS-Mini-project-2-instructions.pdf).\n\nFor any additional question, please email the course instructor at luigi.acerbi@unige.ch.\n\n## License\n\nCode and scripts in this repository are released under the terms of the [MIT License](https://github.com/lacerbi/tics-2020-tutorial/blob/master/LICENSE).\n\n","funding_links":[],"categories":[],"sub_categories":[],"project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Flacerbi%2Ftics-2020-tutorial","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Flacerbi%2Ftics-2020-tutorial","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Flacerbi%2Ftics-2020-tutorial/lists"}