Instructor: Alejandro Correa Bahnsen
- email: al.bahnsen@gmail.com
- twitter: @albahnsen
- github: albahnsen
- Python version 3.5;
- Numpy, the core numerical extensions for linear algebra and multidimensional arrays;
- Scipy, additional libraries for scientific programming;
- Matplotlib, excellent plotting and graphing libraries;
- IPython, with the additional libraries required for the notebook interface.
- Pandas, Python version of R dataframe
- Seaborn, used mainly for plot styling
- scikit-learn, Machine learning library!
A good, easy to install option that supports Mac, Windows, and Linux, and that has all of these packages (and much more) is the Anaconda.
GIT!! Unfortunatelly out of the scope of this class, but please take a look at these tutorials
| Session | Notebook link | Exercises |
|---|---|---|
| 1 | Introduction to Python | 01.1 - Finding digits of Pi, 01.2 - OLS and Numpy |
| 2 | Introduction to Machine Learning | 02 - Churn Model |