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The Science Behind An Algorithm And Its Functions
Even if you don't have the faintest idea about technical jargon like AI, Big Data, or Machine Learning, you must still be familiar with the word algorithm. Be it high-end supercomputers or something as simple as a mobile app, everything has an algorithm backing them. In simple words, an algorithm is a set of instructions given to a computer system to complete a task or convert data into useful information for users.

A good way to think of an algorithm is as a manual that tells a computer to solve a problem by manipulating the given data. There are many instances where we use an algorithm, for example, finding routes on the maps app or displaying information on a display. A search engine is also an algorithm that takes a query as input and looks for relevant information in the database and shows the results as an output. But have you ever wondered what goes behind the curtains? Let's dive into the details.

Information Is The Key
When you spend money from your savings, what information do you require? Most importantly, you need to know the available sum in your account. Then you might consider your upcoming expenses, and then maybe other preferences. Similarly, a computer requires such inputs that will help it make a decision. All this can come in the form of data, which is a collection of numbers or words.
A good algorithm defines the input and the output with precision, making each step clear and unambiguous. Besides, an algorithm shouldn't have a computer code, rather it should be written in a way that comes in handy for different programming languages.

Computations Play Huge Part
This is where the magic happens! This part involves arithmetic and decision-making. The system makes decisions by doing the math of the provided data. So how does it apply to spending money? You decide to withdraw an amount by doing some calculations with the available information. That's what an algorithm does to make a decision.
Automation software is a great example of an algorithm in action. Automation follows a set of rules to accomplish a task and those rules form an algorithm. For instance, one of the apps on your phones requires automation software to categorize all billing information received via email or text and put it into a separate sheet. To achieve this, a series of rules are set for the program to follow - an algorithm.

The Final Step
Output or the result is the final stage of an algorithm. Out enables systems to merge algorithms in a more complex way to produce more algorithms. Besides, output also involves providing information, for instance showing information on a screen.
However, there are times when the decision-making process becomes too complicated. That's where the machine learning algorithm comes in. Machine learning algorithm tries to learn from the past decisions of the system and offers an output. It's commonly used for search engines where recommendations and searching for information are heavily involved.
For our money expenditure example, a machine learning algorithm will provide you information based on your previous expenditure patterns, allowing you to manage your expenses better. An algorithm might involve a simple process of converting input into output, but it plays a huge part in every place where technology exists. Maybe next time you see a computer solve a complex number-crunching task in seconds, you can appreciate the algorithm behind it.
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