Basics of Machine Learning and it's Algorithms -You Need to Know

Basics of Machine Learning and it's Algorithms -You Need to Know

In this blog you will learn about machine learning and it’s algorithms. By the end of the blog, you will have the basic understanding of this field Hi folks! Are you intrigued about Machine Learning and its Algorithms? If yes, Welcome. You have come to the

Are you intrigued about Machine Learning and its Algorithms?

If yes, Welcome. You have come to the right place. In this blog you will learn about machine learning and it’s algorithms. By the end of the blog, you will have the basic understanding of this field

Machine Learning

The term is self-explanatory enough that there is going to be a machine that will learn something. The machine is a computer and how it’s going to learn is something that is going to be interesting to know. So let’s dive into the ocean of machine learning.

In a layman’s definition, machine learning is nothing but a machine that tries to mimic human beings. Machines try to analyze the situation and predict the result just like us. The major difference between human thinking and machine thinking is, humans have brains to think and analyze but machines do not have a brain. So algorithms and models work as the brain for them. The machines are trained by using those algorithms and models in such a way that they become capable of analyzing the data provided to them and give human-like responses which are more accurate when there is a huge amount of data given.

As humans are just not capable of analyzing and handling an abundant amount of data, machine learning is one such technology that can overcome this human drawback. Just like humans machines also learn with their experiences, some amount of input is provided to the machines, and the performance increases after each try.

To understand the working of machine learning let’s see a real-life example:

When we play some sport, say basketball and initially, you don’t know much about it so you break a lot of rules and make mistakes. On the second try, you improve on those mistakes but tend to make new ones. But try after try we get familiar with how to play the sport. So it’s continuous experience and learning. In the same way, the machine also learns to try after try and finally give good results.

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