Update tech_docs/math_objects_python.md

tech_docs/math_objects_python.md

@@ -7,7 +7,7 @@ This document explains different types of mathematical objects and their applica
 A **scalar** is a single number, typically used in mathematics to represent a magnitude or quantity. In programming and data science, scalars are often used as individual data points or constants.
 
 ### Example
-```latex
+```
 $$ a = 3 $$
 ```
 
@@ -19,7 +19,7 @@ $$ a = 3 $$
 A **vector** is an ordered array of numbers, which can represent direction and magnitude in space. Vectors are fundamental in physics for describing velocities and forces, in engineering for load distributions, and in machine learning for feature representation.
 
 ### Example
-```latex
+```
 $$ \mathbf{v} = \begin{bmatrix} 1 \\ 2 \\ 3 \end{bmatrix} $$
 ```
 
@@ -32,7 +32,7 @@ $$ \mathbf{v} = \begin{bmatrix} 1 \\ 2 \\ 3 \end{bmatrix} $$
 A **matrix** is a two-dimensional array of numbers used extensively in engineering, physics, computer science, and statistics. Matrices are crucial in solving systems of linear equations, transforming geometric data, and in algorithms for machine learning and artificial intelligence.
 
 ### Example
-```latex
+```
 $$ \mathbf{M} = \begin{bmatrix} 1 & 2 \\ 3 & 4 \end{bmatrix} $$
 ```
 
@@ -46,7 +46,7 @@ $$ \mathbf{M} = \begin{bmatrix} 1 & 2 \\ 3 & 4 \end{bmatrix} $$
 A **tensor** extends the concept of vectors and matrices to potentially higher dimensions. In the field of machine learning and neural networks, tensors are key structures, representing complex datasets and the parameters of the models themselves.
 
 ### Example
-```latex
+```
 $$ \mathcal{T} = \begin{bmatrix} 
 \begin{bmatrix} 1 & 2 \\ 3 & 4 \end{bmatrix} & 
 \begin{bmatrix} 5 & 6 \\ 7 & 8 \end{bmatrix} \\