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matrix multiplication calculator

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Okay, let's dive into building a matrix multiplication calculator with a detailed explanation and Python code examples.

**What is Matrix Multiplication?**

Matrix multiplication is a fundamental operation in linear algebra. It's a way to combine two matrices to produce a new matrix. It's used extensively in computer graphics, data analysis, machine learning, and many other fields.

**Key Concepts and Requirements**

1. **Compatibility:** Matrix multiplication is only defined when the number of columns in the first matrix equals the number of rows in the second matrix. If matrix A has dimensions (m x n) and matrix B has dimensions (n x p), then the product AB is defined and will have dimensions (m x p).
2. **Calculation:** Each element in the resulting matrix is calculated as the sum of the products of the elements in the corresponding row of the first matrix and the corresponding column of the second matrix.
* `result[i][j] = sum(A[i][k] * B[k][j] for k in range(n))`
3. **Order Matters:** In general, `AB` is not equal to `BA`. Matrix multiplication is *not* commutative.

**Steps to Build a Matrix Multiplication Calculator**

Here's a breakdown of the steps we'll take to create our matrix multiplication calculator:

1. **Input Matrices:**
* Get the dimensions of the two matrices (number of rows and columns).
* Get the elements of the matrices from the user or some data source.
2. **Validation:**
* Check if the matrices are compatible for multiplication (number of columns in the first matrix equals the number of rows in the second matrix). If not, display an error message and exit.
3. **Multiplication:**
* Create a new matrix to store the result.
* Implement the matrix multiplication algorithm to calculate the elements of the result matrix.
4. **Output:**
* Display the resulting matrix in a readable format.

**Python Code Implementation**

Here's a Python code example with detailed comments:
**Explanation of the ...

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Видео matrix multiplication calculator канала CodeMind
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