NumPy stands for numerical python and is a python library used for working with arrays. It has functions for working in the domains of linear algebra, fourier transform and matrices. It was created in 2005 by Travis Oliphant and is an open source project that can be used freely. Why Use NumPy Python has lists that serve the purpose of arrays but they are slow too process. NumPy aims to provide an array object that is up to 50x faster than traditional python lists. the array object in NumPy is called ndarray. It provides a lot of supporting functions that make working with ndarray very easy. NumPy arrays are stored at one continuous place in memory unlike lists, so processes can access and manipulate them very efficiently. this behaviour is called locality of reference in computer science. It is also optimized to work with the latest CPU architecture. This is why NumPy is faster than lists. NumPy is written partially in python but most of the parts that require fast computation are writ

Git is the free and open source distributed version control system that's responsible for everything GitHub related that happens locally on your computer. This cheat sheet features the most important and commonly used Git commands for easy reference. SETUP set a name that is identifiable for credit when review version history. git config --global user.name “[firstname lastname]” set an email address that will be associated with each history maker. git config --global user.email “[valid-email]” set automatic command-line colouring for Git for easy reviewing. git config --global color.ui auto SETUP & INIT initialize an existing directory as a Git repository git init Retrieve an entire repository from a hosted location via URL. git clone [url] STAGE & SNAPSHOT Show modified files in working directory, staged for your next commit. git status Add a file as it looks now to your next commit. git add [file] Unstage a file while retaining the changes in working