/python_lecture

Introduction to Python.
  1. Python 100.0%
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figures
logreg
.gitignore
01_python.ipynb
01_python.slides.html
02_numpy.ipynb
02_numpy.slides.html
03_logreg.ipynb
03_logreg.slides.html
04_sympy.ipynb
04_sympy.slides.html
RCC-Auto-Diff-presentation.pdf
README.rst
requirements.txt

README.rst

Python lecture

Introduction to Python, NumPy, and SymPy.

  1. Python basics
  2. NumPy
  3. Logistic regression
  4. SymPy

Installation

  1. Install python3.4 on your machine
  2. Clone this repository by git clone https://github.com/cangermueller/python_lecture.git
  3. Install the required packages by pip install requirements.txt
  4. Run ipython notebook