- Git - source code management
- GitHub - code hosting platform (syncing a fork)
The core SciPy stack for working with data in Python:
- Numpy - numpy arrays allow for easy manipulation of data in vectors or matrices. Basic numerical routines are also available, and are optimized for compututational efficiency.
- Scipy - a library of functions for scientific computing.
- Matplotlib - a plotting library that enables the creation of very customizable plot.
- IPython - an interactive python shell.
- Pandas - a package that provides data structures optimal for working with tabular data.
Tutorials for numpy, scipy, sympy, scikit-learn, and matplotlib
- Jupyter Notebook - Web application that can contain live code, visualizations, and text. It supports many programming languages; we will use it with the Python 3 kernel.
- Cookiecutter Data Science - A project structure to standardize your data science project.