I joined Quansight at the beginning of April, splitting my time between PyTorch (as part of a larger Quansight team) and contributing to Quansight Labs supported community-driven projects in the Python scientific and data science software stack, primarily to NumPy.
I joined Quansight at the beginning of April, splitting my time between PyTorch (as part of a larger Quansight team) and contributing to Quansight Labs supported community-driven projects in the Python scientific and data science software stack, primarily to NumPy. I have found my next home; the people, the projects, and the atmosphere are an all around win-win for me and (I hope) for the projects to which I contribute.
I am not a newcomer to Open Source. I originally became involved in PyPy as an after-hours hobby to hone my developer skills, and quickly became enamoured with the people and the mission. Over the years my efforts in the open source world moved more mainstream, and in 2018 I took on a full-time position working on NumPy, funded through a grant to BIDS. Since April 2020, I have moved to Quansight Labs as a full-time developer.
Learn numpy features to see why you should use numpy - high performance, multidimensional container, broadcasting functions, working with varied databases
Learn the uses of numpy - Alternate for lists in python, multi dimensional array, mathematical operations. See numpy applications with python libraries.
Learn NumPy Copy and View - Deep Copy, shallow copy and No copy in NumPy, NumPy view creation and types with examples, NumPy View vs Copy
Python is an open-source object-oriented language. It has many features of which one is the wide range of external packages. There are a lot of packages for installation and use for expanding functionalities. These packages are a repository of functions in python script. NumPy is one such package to ease array computations.
Learn about NumPy Array, NumPy Array creation, various array functions, array indexing & Slicing, array operations, methods and dimensions,It also includes array splitting, reshaping, and joining of arrays. Even the other external libraries in Python relate to NumPy arrays.