What is Symbolic Computation in Sympy

Recipe Objective - What is Symbolic Computation in Sympy?

Symbolic computing refers to the development of algorithms for manipulating mathematical expressions and other mathematical objects. Symbolic computing integrates mathematics with computer science to solve mathematical expressions using mathematical symbols. A Computer Algebra System (CAS), as SymPy, evaluates algebraic expressions exactly (not approximately) using the same symbols used in the traditional manual method.

For more related projects -

https://www.projectpro.io/projects/data-science-projects/tensorflow-projects
https://www.projectpro.io/projects/data-science-projects/keras-deep-learning-projects

For example, we calculate the square root of a number using Python's math module as follows:

import math
print("Square root of 9 => ",math.sqrt(9))
print("Square root of 11 => ",math.sqrt(11))


Output - 
Square root of 9 =>  3.0
Square root of 11 =>  3.3166247903554

As you can see, the square root of 11 is roughly estimated. But in SymPy, square roots of numbers that are not perfect squares are left unexamined by default, as follows:

import sympy
print("Square root of 9 => ",sympy.sqrt(9))
print("Square root of 11 => ",sympy.sqrt(11))


Output - 
Square root of 9 =>  3
Square root of 11 =>  sqrt(11)