ImageXD 2016
============

This course material is available at
https://github.com/scikit-image/skimage-tutorials

Welcome to BIDS!
----------------

Welcome to the `Berkeley Institute of Data Science
<https://bids.berkeley.edu>`__ on the campus of the University of
California at Berkeley.

  - Restrooms are out the back door of BIDS, down the corridor to the
    right (i.e., at the southern entrance of the Doe Library).  **You
    cannot re-enter BIDS through the back door--please take the
    (inside) corridor to the front entrance**.

  - Wifi is available via the CalVisitor hotspot.

Conversation
````````````
During the tutorial, there will be an open Etherpad at
https://public.etherpad-mozilla.org/p/imagexd where you can make notes
and communicate with classmates.


Schedule
--------

- 09:30—10:00  :doc:`Introduction <lessons/0_introduction>` & :doc:`preparation <lessons/0_preparation>`
- 10:00—10:45  :doc:`Advanced NumPy <lessons/1_advanced_numpy>`
- 10:45—11:00  Coffee break
- 11:00—11:30  :doc:`Advanced NumPy <lessons/1_advanced_numpy>`
- 11:30—12:15  `Matplotlib <http://cbio.ensmp.fr/~nvaroquaux/teaching/2016-image-xd/intro/matplotlib/matplotlib.html>`_

----

- 12:15—13:15  Lunch

----

- 13:15—14:00  `SciPy overview <http://cbio.ensmp.fr/~nvaroquaux/teaching/2016-image-xd/intro/scipy.html>`_
- 14:00—14:30  :doc:`scikit-image: images are arrays <lessons/0_images_are_arrays>`
- 14:30—14:45  Coffee break
- 14:45—15:45  scikit-image: `filtering
  <http://nbviewer.jupyter.org/github/scikit-image/skimage-tutorials/blob/master/book/lessons/1_image_filters.ipynb>`__
  and `segmentation
  <http://nbviewer.jupyter.org/github/scikit-image/skimage-tutorials/blob/master/book/lessons/4_segmentation.ipynb>`__
- 15:45—16:15  :doc:`scikit-image: RANSAC <lessons/1_ransac>`
- 16:15—16:25  Coffee break
- 16:25—16:30  Panorama demo
- 16:30—17:00  `Introduction to scikit-learn <http://cbio.ensmp.fr/~nvaroquaux/teaching/2016-image-xd/intro/sklearn.html>`_
- 17:00—17:30  Demo: scikit-learn with scikit-image

.. toctree::
   :hidden:
   :maxdepth: 1

   lessons/0_introduction
   lessons/0_preparation
   lessons/1_advanced_numpy
   Matplotlib <lessons/matplotlib/matplotlib>
   lessons/0_images_are_arrays
   lessons/1_ransac