Evolutionary Computation with IPython
IPython notebooks about genetic and evolutionary computation
Luis Martí, DEE, PUC-Rio http://lmarti.com
This repository contains the IPython notebooks that are used in the demonstrations classes of my course "Advanced Evolutionary Computation: Theory and Practice", which is taught as part of the PhD in Electrical Engineering, Department of Electrical Engineering of the Pontifícia Universidade Católica do Rio de Janeiro.
Project web: http://lmarti.github.io/evolutionary-computation-course/
Available notebooks
- AEC.01 - A Fast (and Furious) Introduction to Python.ipynb
- AEC.02 - Elements of Evolutionary Algorithms.ipynb
- AEC.03 - Solving the TSP with GAs.ipynb
- AEC.04 - Evolutionary Strategies and Covariance Matrix Adaptation.ipynb
- AEC.06 - Evolutionary Multi-Objective Optimization.ipynb
A note on viewing the notebooks
Notebooks are meant to be viewed as slides. That is why they contain relatively few text and mostly graphical information. However, nothing stop you from viewing them as regular notebooks.
Online viewing
Notebooks converted to static html slides:
- AEC.01 - A Fast (and Furious) Introduction to Python
- [AEC.02 - Elements of Evolutionary Algorithms](http://lmarti.github.io/evolutionary-computation-course/AEC.02 - Elements of Evolutionary Algorithms.slides.html)
- [AEC.03 - Solving the TSP with GAs](http://lmarti.github.io/evolutionary-computation-course/AEC.03 - Solving the TSP with GAs.slides.html)
- [AEC.04 - Evolutionary Strategies and Covariance Matrix Adaptation](http://lmarti.github.io/evolutionary-computation-course/AEC.04 - Evolutionary Strategies and Covariance Matrix Adaptation.slides.html)
- [AEC.06 - Evolutionary Multi-Objective Optimization](http://lmarti.github.io/evolutionary-computation-course/AEC.06 - Evolutionary Multi-Objective Optimization.slides.html)
Another option is to use the IPython notebook slide viewer (a slides equivalent of nbviwer.ipython.org). However, bear in mind that this is a development version and some slides of the notebook might not be properly rendered.
Offline (local) slides
- You can convert them to slides and view them locally by using
nbconvertwith a command like:
$ ipython nbconvert --to slides --post serve <a-notebook-name.ipynb>
- Another -very cool- option is to install Reveal.js - Jupyter/IPython Slideshow Extension for a (very cool) live view where you can actually execute the notebook in slide mode. This is the one I use in class.