Python SimPy Complete Tutorial For Machine Learning

 

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SymPy is a Python library for symbolic mathematics. It aims to become a full-featured computer algebra system (CAS) while keeping the code as simple as possible in order to be comprehensible and easily extensible. SymPy is written entirely in Python.

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SymPy Tutorial

• Preliminaries
  • Installation
  • Exercises
  • About This Tutorial
• Introduction
  • What is Symbolic Computation?
  • A More Interesting Example
  • The Power of Symbolic Computation
  • Why SymPy?
• Gotchas
  • Symbols
  • Equals signs
  • Two Final Notes: ^ and /
  • Further Reading
• Basic Operations
  • Substitution
  • Converting Strings to SymPy Expressions
  • evalf
  • lambdify
• Printing
  • Printers
  • Setting up Pretty Printing
  • Printing Functions
• Simplification
  • simplify
  • Polynomial/Rational Function Simplification
  • Trigonometric Simplification
  • Powers
  • Exponentials and logarithms
  • Special Functions
  • Example: Continued Fractions
• Calculus
  • Derivatives
  • Integrals
  • Limits
  • Series Expansion
  • Finite differences
• Solvers
  • A Note about Equations
  • Solving Equations Algebraically
  • Solving Differential Equations
• Matrices
  • Basic Operations
  • Basic Methods
  • Matrix Constructors
  • Advanced Methods
  • Possible Issues
• Advanced Expression Manipulation
  • Understanding Expression Trees
  • Recursing through an Expression Tree
  • Prevent expression evaluation

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