Material developed for Texas A&M University - Commerce course CSci 560: Neural Networks
Viewing the notebooks online
Suggested material for learning python:
- Think Python: How to think like a computer scientist free online textbook, very good resource for not only Python but learning to program in general.
- Google Developers Python Class short course with videos, might be helpful for those looking for video tutorials of Python.
- Software Carpentry section on learning Python is also very good, and also includes videos.
Companion Textbooks on Machine Learning:
Segaran. (2007). Programming Collective Intelligence. Already 6 years old, so a bit out of date, and as far as I know no new editions. But I will develop some of my optimization and decision tree examples from here. Code examples
Conway & White. (2012). Machine Learning for Hackers. github repo of book source and data Case studies for this book are written in R. This site Will it Python has example reimplementations in iPython notebooks.
For a true interactive use of the notebooks (which you are required to use if you are taking the class) you need to install Python, IPython (for notebooks) and the required libraries scikit-learn, matplotlib and numpy.
You can install everything at once using a complete scientific Python distribution. Two good ones are the Enthought Python distribution (EPD, free for academic use) or Python-(x, y) (free for everyone).
Just use your package manager, for example on ubuntu or debian, use
apt-get install python ipython python-matplotlib python-numpy python-sklearn.
You need to make sure to have at least IPython >= 0.11 installed. You can update using the programm
More tips on installing scikit-learn can be found on the scikit-learn website. If you used the Enthought Python distribution, I believe they will be installed for you as part of that distribution.