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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
    • Basic Python Datatypes
    • Advanced Datatypes
    • Control Flow
    • Exercises
  • Functions and Classes
    • Functions
    • Exercises
    • Classes
    • Modules
    • Practicing Classes
  • Miscellaneous
    • Exceptions
    • Print
    • Exercises

Arrays

  • NumPy
    • NumPy
    • NumPy Advanced Operations
    • NumPy exercises

Scientific Python

  • matplotlib
    • matplotlib
    • matplotlib exercises
  • SciPy
    • SciPy
    • SciPy exercises
    • More SciPy
    • More SciPy Exercises
  • 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

Git and Github

  • Version Control
  • A Git Walkthrough
  • github
  • Pull requests

Unit tests

  • Testing
  • pytest
    • More pytest
  • Real World Example

Extensions

  • Extensions
  • Example Extension
  • Repository
  • Open issue

Index

By Michael Zingale

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