What is an algorithm? Simple and easy explanation for beginners

What is an algorithm?

Simply put, an algorithm is a computer’s exact guide, including a step-by-step process for performing input tasks to deliver the expected result. This solving process consists of a limited series of instructions so that the computer knows how to approach a problem and presents the results accordingly

The development of new algorithms has speeded up the computing process. However, you must know which algorithm to choose for any task. Basically, an algorithm can be a digital map designed to solve logical and mathematical equations in natural languages.

The importance of the algorithm

Being the backbone of computer operations, algorithms tell the best and easiest ways to solve a problem, and they come to their excellent result. From increasing software accuracy by enhancing the source program to completing tasks with limited resources (such as memory power), algorithms can improve the efficiency of software and computational operations.

Simplified variants of algorithms broken down into smaller steps help programmers to understand and create efficient computer programs. Algorithms are language independent, accept steps to be performed in any language but lead to the desired result.

Algorithm properties

Not all written instruction sequences are algorithms. Several features make the instruction set qualified as an algorithm. For a series of instructions that is an algorithm, these are basic properties.

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• Inputs: An algorithm must have well-defined inputs, generally more than one.
• Output: The expected output must be clearly defined by the algorithm.
• Unambiguous: an algorithm written should not be ambiguous at all. You must have the right steps for programmers to follow and achieve effective results.
• Delimited: Instead of infinite loops and each step with double meaning, delimited algorithms should only carry one interpretation with each statement.
• Limited: To reach an effective solution, the steps of the algorithm must be finite and well defined.
• Practical: the algorithm must match existing resources to remain efficient and make the most of them.
  

Different ways to represent algorithms

Algorithms can be represented in four different ways. These include:

Natural language

Regularly exchanged natural languages, such as English, French, Spanish, etc., can also represent algorithms. As long as the programmer understands the carefully drawn steps, this is acceptable. However, natural languages ​​often lack the precision required by computer programs, and are therefore not highly favored.

False code

This informal way of representing the algorithm uses natural language minus its ambiguous parts. The pseudocode presents the instructions in a more accurate form.

Flow charts

The graphic represents programming in a flow format to simplify understanding. The illustration of the algorithms in this graphic format uses different symbols and boxes, which limits interpretations and provides precise meaning.

Programming languages

Algorithms written in programming languages ​​are ready to become a program. With a few changes and fixes, algorithms written in a programming language are ready to go.

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What is an algorithm in programming?

In addition to solving basic arithmetic commands, algorithms aid in software development by executing simple and complex instructions. The algorithm plays an important role in programming, as it is used at the design stage and preceded by its implementation in the project at the programming stage.

To understand it better, algorithms work like code to instruct a software program to perform certain tasks. For example, Google displays the most relevant search results based on detailed algorithms to find, rank and display the pages most relevant to the search keyword. Lack of proper algorithms can lead to confusing and inappropriate page results.

The role of algorithms in artificial intelligence

Artificial intelligence relies on simulating human intelligence to perfect the delivery of innovative, personalized and user-friendly services. Integrating AI into everyday life has simplified many tasks, from suggesting relevant products for our search algorithm to monitoring our vital signs. It’s hard to imagine a life without artificial intelligence in the 21st century, but what is the technology behind it?

AI cannot access the information on its own. Just as we slowly understand how the world works and operates according to it, AI must learn to simulate human intelligence through basic instructions. This is where the algorithms come into the picture.

Algorithms are basically precise instructions that train an AI to read, analyze, and perform related tasks and operations. An artificial intelligence algorithm is a subset of machine learning that is a device to imitate human intelligence and perform tasks independently. A good example is the smart virtual assistants that play songs with one command or recommend playlists based only on your search history and pages that interest you. Moreover, these processors can also distinguish between different sounds – imagine the level of complexity of the algorithms used to make this possible!

Types of algorithms

There are several types of algorithms that are used to solve calculus problems using different methods. The most used are:

Backtracking algorithm

This algorithm divides and solves the subproblem of any equation. For example, you are trying to solve a problem, and if you can’t, go back by deleting the last step and then try to solve the problem again.

Brute force algorithm

This algorithm iterates through all possible solutions, just as we do, and finds the most relevant solution to solve the problem. It is one of the simplest algorithms.

Divide and conquer algorithm

As the name implies, this algorithm divides the problem into two parts. Then you try to solve the first half into smaller sub-problems and do the same for the other half, only to combine all the solutions to create the resulting solution.

Dynamic programming algorithm

Dynamic programming algorithms use historical data to analyze and solve a specific problem. Divide the problem into sub-problems, figure out each part of the problem, and then store the pattern for future use.

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Recursive algorithm

A recursive algorithm solves a problem by dividing it into sub-problems of similar types and then calling itself over and over until the problem is completely solved.

Greedy algorithm

Greedy algorithms follow a problem-solving pattern that works piece by piece and matches a solution that generates instant gains. Your goal is to find the optimal solution locally, but often you can’t find it because you don’t go through all the data.

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Conclusion

Bottom line: Algorithms are the building blocks of all computer operations, whether it’s a simple computer program or an ML program. Algorithms are essential for all computing devices as they can automate various tasks, perform repetitive tasks efficiently, reduce reliance on manual labor, and simplify the entire process. They can save time and money.