Hits: 10

# Java Program to Multiply two Matrices by Passing Matrix to a Function

#### In this program, you’ll learn to multiply two matrices using a function in Java.

For matrix multiplication to take place, the number of columns of the first matrix must be equal to the number of rows of the second matrix. In our example, i.e.

c1 = r2

Also, the final product matrix is of size `r1 x c2`

, i.e.

product[r1][c2]

## Example: Program to Multiply Two Matrices using a Function

```
public class MultiplyMatrices{
public static void main(String[] args){
int r1 = 2, c1 = 3;
int r2 = 3, c2 = 2;
int[][] firstMatrix = { {3, -2, 5}, {3, 0, 4} };
int[][] secondMatrix = { {2, 3}, {-9, 0}, {0, 4} };
// Mutliplying Two matrices
int[][] product = multiplyMatrices(firstMatrix, secondMatrix, r1, c1, c2);
// Displaying the result
displayProduct(product);
}
public static int[][] multiplyMatrices(int[][] firstMatrix, int[][] secondMatrix, int r1, int c1, int c2) {
int[][] product = new int[r1][c2];
for(int i = 0; i < r1; i++) {
for (int j = 0; j < c2; j++) {
for (int k = 0; k < c1; k++) {
product[i][j] += firstMatrix[i][k] * secondMatrix[k][j];
}
}
}
return product;
}
public static void displayProduct(int[][] product){
System.out.println("Product of two matrices is: ");
for(int[] row : product) {
for (int column : row) {
System.out.print(column + " ");
}
System.out.println();
}
}
}
```

**Output**

Product of two matrices is: 24 29 6 25

In the above program, there are two functions:

`multiplyMatrices()`

which multiplies the two given matrices and returns the product matrix`displayProduct()`

which displays the output of the product matrix on the screen.

The multiplication takes place as:

|^{-}(a_{11}x b_{11}) + (a_{12}x b_{21}) + (a_{13}x b_{31}) (a_{11}x b_{12}) + (a_{12}x b_{22}) + (a_{13}x b_{32})^{-}| |_ (a_{21}x b_{11}) + (a_{22}x b_{21}) + (a_{23}x b_{31}) (a_{21}x b_{12}) + (a_{22}x b_{22}) + (a_{23}x b_{32}) _|

In our example, it takes place as:

|^{-}(3 x 2) + (-2 x -9) + (5 x 0) = 24 (3 x 3) + (-2 x 0) + (5 x 4) = 29^{-}| |_ (3 x 2) + ( 0 x -9) + (4 x 0) = 6 (3 x 3) + ( 0 x 0) + (4 x 4) = 25 _|

# Python Example for Beginners

## Two Machine Learning Fields

There are two sides to machine learning:

**Practical Machine Learning:**This is about querying databases, cleaning data, writing scripts to transform data and gluing algorithm and libraries together and writing custom code to squeeze reliable answers from data to satisfy difficult and ill defined questions. It’s the mess of reality.**Theoretical Machine Learning**: This is about math and abstraction and idealized scenarios and limits and beauty and informing what is possible. It is a whole lot neater and cleaner and removed from the mess of reality.

**Data Science Resources: Data Science Recipes and Applied Machine Learning Recipes**

**Introduction to Applied Machine Learning & Data Science for Beginners, Business Analysts, Students, Researchers and Freelancers with Python & R Codes @ Western Australian Center for Applied Machine Learning & Data Science (WACAMLDS) !!!**

Latest end-to-end Learn by Coding Recipes in Project-Based Learning:

**Applied Statistics with R for Beginners and Business Professionals**

**Data Science and Machine Learning Projects in Python: Tabular Data Analytics**

**Data Science and Machine Learning Projects in R: Tabular Data Analytics**

**Python Machine Learning & Data Science Recipes: Learn by Coding**

**R Machine Learning & Data Science Recipes: Learn by Coding**

**Comparing Different Machine Learning Algorithms in Python for Classification (FREE)**

Disclaimer: The information and code presented within this recipe/tutorial is only for educational and coaching purposes for beginners and developers. Anyone can practice and apply the recipe/tutorial presented here, but the reader is taking full responsibility for his/her actions. The author (content curator) of this recipe (code / program) has made every effort to ensure the accuracy of the information was correct at time of publication. The author (content curator) does not assume and hereby disclaims any liability to any party for any loss, damage, or disruption caused by errors or omissions, whether such errors or omissions result from accident, negligence, or any other cause.The information presented here could also be found in public knowledge domains.