Kotlin example Kotlin tutorials

Kotlin example for Beginners – Kotlin Program to Find G.C.D Using Recursion

By on Thursday, May 6, 2021

Kotlin Program to Find G.C.D Using Recursion

In this program, you’ll learn to find the GCD (Greatest Common Divisor) or HCF using a recursive function in Kotlin.

This program takes two positive integers and calculates GCD using recursion.

 

Example: GCD of Two Numbers using Recursion


fun main(args: Array<String>) {
    val n1 = 366
    val n2 = 60
    val hcf = hcf(n1, n2)

    println("G.C.D of $n1 and $n2 is $hcf.")
}

fun hcf(n1: Int, n2: Int): Int {
    if (n2 != 0)
        return hcf(n2, n1 % n2)
    else
        return n1
}

When you run the program, the output will be:

G.C.D of 366 and 60 is 6.

In the above program, the recursive function is called until n2 is 0. In the end, the value of n1 is the GCD or HCF of the given two numbers.

Execution Steps
No. Recursive call n1 n2 n1 % n2
1 hcf(366, 60) 366 60 6
2 hcf(60, 6) 60 6 0
Final hcf(6, 0) 6 0 –

 

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.
0
Related Posts