Home

Install python on your computer

Everware provides very limited resources. You can use docker (virtual machine) to get the same environment on your computer. Follow this instruction but instead of yandex/rep use arogozhnikov/mlatimperial2016 image.

If you don't like VMs, you can install the necessary scientific infrastructure (mainly numpy, scipy, pandas, scikit-learn packages together with ipython and ipython notebook extensions) on your own computer, the easiest way to do that is to install Anaconda package here. You should select your operating system, python 2. (Important note: some packages recommended through course may not be easy to install with conda)

Additional information sources

Tutorials

• [A Crash Course in Python for Scientists] (http://nbviewer.ipython.org/gist/rpmuller/5920182)
• [Numpy] (https://docs.scipy.org/doc/numpy-dev/user/quickstart.html)
• [Matplotlib] (http://nbviewer.jupyter.org/github/jrjohansson/scientific-python-lectures/blob/master/Lecture-4-Matplotlib.ipynb)
• [Scipy Lecture Notes] (http://www.scipy-lectures.org/)
• [Pandas] (http://pandas.pydata.org/pandas-docs/stable/10min.html)
• [Scikit-learn] (http://scikit-learn.org/stable/tutorial/basic/tutorial.html)

More detailed information

• [A free classical book on machine learning] (http://web.stanford.edu/~hastie/local.ftp/Springer/ESLII_print10.pdf)
• [Official python site] (http://python.org)
• [NumPy] (http://www.numpy.org/) , [Pandas] (http://pandas.pydata.org/), [Matplotlib] (http://matplotlib.org/), [SciKit-Learn] (http://scikit-learn.org/stable/)
• [A gallery of ineresting IPython notebooks] (https://github.com/ipython/ipython/wiki/A-gallery-of-interesting-IPython-Notebooks)