Have you guys ever wondered how Facebook is able to perform facial recognition? Or how companies are able to bombard you with the products all over social media? Have you ever thought how Google’s self drive car would operate if there’s no one driving it?

All of this is because of machine learning. Yes, it literally means a machine that is learning independently and becoming more intelligent. If you are interested to hear more, in this article I will be taking you through some of the important concepts of machine learning.

Machine Learning 101

Machine learning is a method that allows computers to imitate and adapt to human-like behavior. This then allows the machine to analyze past data, learns from that data, and makes decisions or predictions. The computer is training itself to perform the task the right way based on everything it can learn from the past data. The computer is creating its own logical solutions all of which are without any form of human assistance or intervention. Essentially, these systems learn, grow, change, and develop themselves when exposed to new data.

As you can imagine, the methods and capabilities of self learning can vary. Hence, there’s more than one way a machine can learn. If you agree, then let’s dig deeper.

Types of Machine Learning

Machine learning is divided into three major types: supervised learning, unsupervised learning, and reinforcement learning.

1. Supervised Learning

Have you ever imagined how difficult a mail handling would be if Gmail didn’t know what was spam and what wasn’t? Your inbox would be quite the mess wouldn’t it but this is where the first type of machine learning comes in supervised machine learning. The email clients like Microsoft, Outlook, and Gmail use spam filtering methods to ensure that the users are kept safe from spam. These spam filters are regularly kept updated with the help of supervised machine learning.

Supervised machine learning is a method where a model after sufficient training is able to make predictions for the future in a way a question/answer pattern is formed. When a question and answer are given as input the machine learns from it and when a new data is encountered it is able to make a prediction.

2. Unsupervised Learning

Now let’s talk about unsupervised machine learning. Imagine, you just added a photo onto Facebook, as soon as that photo is uploaded there’s a good chance that Facebook is able to identify who’s in the photo and recommend this person be tagged in the photo.

This is done with the help of unsupervised learning; unsupervised learning only deals with input data it ensures that the data is more readable and organized. It analyzes the input data to find out patterns or similarities or anomalies in them. This model is able to learn from observations hence it’s able to find structures and relationships among the input data.

Also, Netflix, Amazon, and several other e-commerce websites use the same method. Hence, you see repeatable up selling patterns arising from it.

3. Reinforcement Learning

The last type of machine learning is reinforcement learning. Supervised learning is about making a prediction and unsupervised learning is about finding a hidden pattern. However, reinforcement learning works completely different.

In fact, it allows the computer to take a decision based on past rewards for its actions but this type of machine learning is usually only to increase the efficiency of a tool or a program.

Benefits of Machine Learning

Machine learning has changed our lives in several significant ways. It allows powerful processing which means it can process through far more complicated data. Hence, the decisions that we make will be much more well-founded and the predictions are much more accurate. Not only does it allow powerful processing but also quicker processing that is more work is done in less a time; the outputs that we obtained are much more accurate.

Now when you think “Big Data” you think a lot of data, this large mass of data has to be stored somewhere. And when this is stored it also has to be managed so with machine learning you can perform affordable data management. A machine learning method is also considerably less expensive, the most important part is as we get more and more data the more and more complex it gets and machine learning allows us to analyze complex “Big Data”.