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PHY 546: Python for Scientific Computing

PHY 546: Python for Scientific Computing

Getting Started

Introduction
Using These Notes
Jupyter

Python Basics

Python Basics
Functions and Classes
Miscellaneous

Arrays

NumPy

Scientific Python

matplotlib
- matplotlib
- matplotlib exercises
SciPy
SymPy
- SymPy examples
- SymPy Exercises

Machine Learning

Artificial Neural Network Basics
- Gradient Descent
- Deriving the Learning Correction
Hidden Layers
- Improvements
Diving Deeper into Machine Learning
- KERAS and MNIST
- Clustering

Python packaging and applications

Python Modules
Command line arguments
Module Paths
Packaging
Tools to Make Your Life Easier

Unit tests

Testing
pytest
- More pytest
Real World Example

Extensions

Extensions
Example Extension

Git and Github

Version Control
A Git Walkthrough
github
Pull requests

Repository
Open issue

.md

Machine Learning

Machine Learning#

We’ll look at a popular library for machine learning.

By Michael Zingale

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