# What is Algorithm | Introduction to Algorithm

12 August 2023

In computer science or any other domain, you might have encountered the term “algorithm,” whether online or during conversations about technology. It’s a term that people use often, but you’ve likely considered its exact meaning. This question has likely crossed your mind multiple times: What are algorithms? How do they work? What are the steps in their working procedure? To begin, let’s start with an Introduction to algorithms.

# What is Algorithm?

In simple terms, we refer to “any series of well-defined steps that outlines a procedure for solving a specific type of problem” as an algorithm. It means if you have a problem, then to solve this particular problem you have to find the solution. So the steps you take to discover the solution are termed algo or algorithm.

Algorithms find use in various fields beyond computer science for problem-solving and process streamlining. They appear in everyday activities such as item sorting, information retrieval, decision-making, as well as more intricate tasks like data analysis, cryptography, and artificial intelligence.

## Use of Algorithms

Algorithms are step-by-step instructions or procedures that computers follow to solve problems or perform specific tasks. They play a fundamental role in various aspects of technology, science, and everyday life.

Here are some common and diverse uses of algorithms:

• Graph Algorithms: Algorithms like Dijkstra’s algorithm and Breadth-First Search are used to find shortest paths, network optimizations, and navigation applications.
• Machine Learning and AI: Various algorithms power machine learning models, including decision trees, neural networks, support vector machines, and clustering algorithms. These algorithms enable tasks like image recognition, language translation, recommendation systems, and more
• Cryptography: Algorithms such as RSA and AES secure communications, data storage, and online transactions by encrypting and decrypting information.
• Natural Language Processing (NLP): Algorithms process and understand human language, enabling applications like sentiment analysis, chatbots, language translation, and speech recognition.
• Bioinformatics: In bioinformatics, researchers use algorithms to analyze biological data, such as DNA sequences, for purposes such as genetic research, drug discovery, and disease diagnosis.
• Sorting and Searching: Algorithms like Bubble Sort, MergeSort, Selection sort and Binary Search are used to organize and retrieve data efficiently. They are essential in databases, file systems, and applications that deal with large datasets.
• Data Compression: Algorithms such as Huffman coding and Lempel-Ziv-Welch (LZW) compress data for efficient storage and transmission. They underpin formats like ZIP and JPEG.
• Graph Algorithms: Algorithms like Dijkstra’s algorithm and Breadth-First Search are used to find shortest paths, network optimizations, and navigation applications.

## How do Algorithms Works?

Algorithm provides a systematic way for computers to process data and make decisions. Here’s a general overview of how algorithms work:

1. Input: Algorithms require input data on which they operate. This data can be in various forms, such as numbers, text, images, or any other relevant information.
2. Processing Steps: Algorithms consist of a sequence of well-defined steps. These steps can involve mathematical operations, logical comparisons, and conditional statements. Designers have crafted each step to transform the input data or steer the decision-making process.
3. Control Flow: Algorithms use control structures to determine the order in which steps are executed. Common control structures include loops (for repeating actions) and conditional statements (for making decisions based on certain conditions).
4. Output: The ultimate goal of an algorithm is to produce an output or a result. This could be a solution to a problem, a transformed set of data, or any other relevant outcome

## What is the Need For Algorithms?

1. Algorithms are necessary for solving complex problems efficiently and effectively.
2. Simple manual methods cannot solve many complex real-world problems. Algorithms offer structured approaches to tackle these complex problems effectively.
3. Algorithms process and analyze data to extract meaningful insights.
4. Algorithms efficiently solve problems by optimizing the use of computing resources such as time, memory, and processing power, enabling tasks to complete in a timely manner.