What is Machine Learning and how it works

Machine Learning is a concept which allows the machine to learn from examples and experience, and that too without being explicitly programmed. So instead of you writing the code, what you do is you feed data to the generic algorithm, and the algorithm/ machine builds the logic based on the given data.

This Blog will help you understand it more clear.

WHAT IS MACHINE LEARNING?

Here are some scenarios where machine learning concept is used in our day to day life:

Whenever we do online shopping while searching for a product we see it recommend us the similar products to the one which we are looking for. And some offers related to that product. These recommendations are done using machine learning concept.

Sometimes you must have noticed that you searched something on google and advertisements related to that application appears on your Instagram account in between the posts. This is all due to the concept of machine learning.

So, Machine learning is an application of Artificial Intelligence that provides the system ability to learn itself from the experience with an explicit program.

TYPES OF MACHINE LEARNING:

The Machine learning concept is sub-categorized into three types:

1.Supervised Learning

2.Unsupervised Learning

3.Reinforcement Learning

Let us understand them one by one:

WHAT IS SUPERVISED LEARNING?

Supervised Learning is the one, where you can consider the learning is guided by a teacher. We have a dataset which acts as a teacher and its role is to train the model or the machine. Once the model gets trained it can start making a prediction or decision when new data is given to it.

WHAT IS UNSUPERVISED LEARNING?

Unsupervised learning allows us to approach problems with little or no idea what our results should look like. We can derive structure from data where we don’t know the effect of the variables.

We can derive this structure by clustering the data based on relationships among the variables in the data. With Unsupervised learning, there is no feedback based on the prediction results.

WHAT IS REINFORCEMENT LEARNING?

Reinforcement Learning is, how the machine trains itself using trial and error. The machine mainly learns from past experiences and tries to perform the best possible solution to a certain problem.

Few examples in our day to day life where Machine Learning is used:

Siri, Alexa, Google Assistant, Samsung Bix By, Traffic Prediction while using online commuting apps, you may know suggestions on social media, etc

Except for the examples shared above, there are a number of ways where machine learning has been proving its potential.

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