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Introduction, Python, images

Course introduction

• what we are going to teach;
• why we are teaching this way;
• structure of classes and homework;
• what the final project will look like (see Projects);
• grading (see Logistics).

Introduction talk slides:

• slides as PDF;
• slides as Markdown source.

Teaching and exercises

• What is an image?;
• Brisk introduction to Python;
• (see also Introduction to Python for beginners for a slightly shorter and less comprehensive version of Brisk introduction to Python).

To start the exercise, open your terminal and type:

pip3 install --user ipython
git clone https://github.com/psych-214-fall-2016/classwork.git
cd classwork/day_00

Then:

atom first_python.py

If we have time, we will start the introduction to the numpy data library, from the numpy introduction of the scipy lecture notes.

• The lecture on the numpy array object;
• Some of the lecture on numerical array operations.

Reading and homework

Please read:

• Donoho et al 2009 [DMR+09] (you can skip-read the sections on Sparselab, Symmlab and Spherelab);
• Preeyanon et al 2014 [PPB14];
• Wilson et al 2014 [WAB+14].

From these papers choose one recommendation for research practice and write:

• one to two paragraphs giving the strongest case you can make for not using that practice;
• one to two paragraphs giving the strongest refutation you can for your first paragraph.