Understanding the way of Machine Learning

Machine learning (ML) has become one of the hottest topics in the tech industry and rightfully so! After all, machine learning has made so many innovations possible. It is, quite honestly, building the future.

However, if you are new to this fascinating and complex world of technology and are wondering what exactly machine learning is, this article is for you! Today, we will tell you more about machine learning and how it works in the simplest way possible.

Keep reading!

What exactly is machine learning?

Simply put, machine learning is a branch of artificial intelligence (AI) that trains machines or computers to automatically learn from a given set of data and past experiences.

The term “machine learning” was coined by American IBMer Arthur Samuel in 1959. He was a computer gaming expert and described machine learning as “a field of study that gives computers the ability to learn without being explicitly programmed”.

In short, we can say that, in machine learning, programmers leverage complex algorithms that enable machines to “learn” from past data without the need for a predetermined equation acting as a model. With time, these machines become smarter and are eventually able to identify patterns and make accurate predictions with minimum human intervention.

Currently, you can find real-life examples of machine learning almost everywhere. Self-driving cars, suggestions made by YouTube or Netflix, or the face recognition feature of your smartphone are nothing but real-life use cases of machine learning.

How does machine learning work?

Data plays the most important role in the field of machine learning. High-quality and reliable data is an important part of any data science engagement. To gain actionable insights, the correct data must be sourced and cleansed before it can be used. Machine learning helps data experts discover and generalize patterns in the data and how it aligns with their business problems.

Generally, to make accurate predictions, a machine can be trained in three different ways:

  • Supervised learning: It is a type of machine learning method where machines are trained through labelled data sets. What happens here is the learning algorithm uses a labelled set of input data and the correct output of that data. This enables it to train an ML model with the help of input and its corresponding output and help it in generating the right predictions.
  • Unsupervised learning: It is a type of machine learning method where only the input data is available while the corresponding output is unavailable. The dataset is unlabeled, and the machine is trained without any supervision. In this method, the machine learning algorithms learn to make predictions by analyzing similarities, differences, and other patterns present in the available dataset.
  • Reinforcement learning: This type of machine learning is best described as “feedback-based” learning. Here, the machine learning algorithm is not provided with any type of dataset. Instead, it is encouraged to observe its surroundings and learn through trial-and-error methods. Consider the example of YouTube or Netflix that suggests new videos or shows based on what you have previously watched.

Machine Learning is the future

So, there you go! That was all about machine learning and how the machine learning algorithm works. With so many incredible benefits, machine learning is becoming more and more popular in every sector.

Considering the advancements machine learning is making every single day, there are no doubts that ML along with artificial intelligence will significantly affect the human world in the near future.

We hope you found this piece helpful and that we were able to provide you with some valuable information about machine learning and the way machine learning algorithms actually work. If you would like to have more information about Machine learning you can book an appointment with our professional experts here.

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