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Title: Python Workshop Follow-Up
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Title: Python Workshop 3 - NumPy
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Author: Thomas J Kennedy
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Email: tkennedy@cs.odu.edu
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---
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| ... | ... | @@ -32,11 +32,9 @@ interests are Rust (at the time of writing) and Python (specifically the NumPy l |
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## Referenced Courses & Materials
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I will reference materials (e.g., lecture notes) and topics from various courses, including:
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I may reference materials (e.g., lecture notes) and topics from various courses, including:
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- **CS 330 - Object Oriented Programming & Design**
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- [S.O.L.I.D](https://www.cs.odu.edu/~tkennedy/cs330/f20/Public/reviewSOLID/)
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- [Iterators](https://www.cs.odu.edu/~tkennedy/cs330/f20/Public/designDiscussionIterators/)
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- **CS 350 - Introduction to Software Engineering**
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- **CS 417 - Computational Methods & Software**
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- [Python non-linear solver discussion](https://www.cs.odu.edu/~tkennedy/cs417/f20/Public/solverDiscussion/)
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| ... | ... | @@ -45,10 +43,31 @@ I will also reference a couple examples from the previous: |
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- [Git workshop](https://www.cs.odu.edu/~tkennedy/git-workshop)
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- [Python workshop](https://git-community.cs.odu.edu/tkennedy/python-workshop/-/wikis/Python-Workshop)
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- [Python workshop](https://git-community.cs.odu.edu/tkennedy/python-workshop/-/wikis/Python-Workshop-2)
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- [Python follow-up workshop](https://git-community.cs.odu.edu/tkennedy/python-workshop/-/wikis/Python-Workshop-2)
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- [Rust workshop](https://www.cs.odu.edu/~tkennedy/rust-workshop)
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## The Broad Strokes
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I will focus on:
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# Overview
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*What is [NumPy](https://numpy.org/)?*
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> According to the official NumPy documentation:
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>
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> NumPy is the fundamental package for scientific computing in Python. It is a
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> Python library that provides a multidimensional array object, various derived
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> objects (such as masked arrays and matrices), and an assortment of routines for
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> fast operations on arrays, including mathematical, logical, shape manipulation,
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> sorting, selecting, I/O, discrete Fourier transforms, basic linear algebra,
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> basic statistical operations, random simulation and much more.
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>
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>
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> Retrieved from <https://numpy.org/doc/stable/user/whatisnumpy.html>
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