# Java Program to Calculate the Sum of Natural Numbers

#### In this program, you’ll learn to calculate the sum of natural numbers using for loop and while loop in Java.

The positive numbers 1, 2, 3… are known as natural numbers and its sum is the result of all numbers starting from 1 to the given number.

For n, the sum of natural numbers is:

1 + 2 + 3 + ... + n

## Example 1: Sum of Natural Numbers using for loop

```
public class SumNatural{
public static void main(String[] args){
int num = 100, sum = 0;
for(int i = 1; i <= num; ++i)
{
// sum = sum + i;
sum += i;
}
System.out.println("Sum = " + sum);
}
}
```

**Output**

Sum = 5050

The above program loops from 1 to the given `num`(100) and adds all numbers to the variable `sum`.

You can solve this problem using a while loop as follows:

## Example 2: Sum of Natural Numbers using while loop

```
public class SumNatural{
public static void main(String[] args){
int num = 50, i = 1, sum = 0;
while(i <= num)
{
sum += i;
i++;
}
System.out.println("Sum = " + sum);
}
}
```

**Output**

Sum = 1275

In the above program, unlike a for loop, we have to increment the value of `i` inside the body of the loop.

Though both programs are technically correct, it is better to use for loop in this case. It’s because the number of iteration (up to `num`) is known.

Visit this page to learn *how to find the sum of natural numbers using recursion*.

# 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.