Difference Between Machine Learning Artificial Intelligence Deep Learning

Hello guys, welcome back to my blog. In this article, I will discuss the difference between machine learning, artificial intelligence, and deep learning, applications, definitions, etc.

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Difference Between Machine Learning, Artificial Intelligence, And Deep Learning

What Is Artificial Intelligence?

Artificial intelligence is a simulation of human intelligence into the machines which are programmed to think according to the humans and mimic their actions.

Artificial intelligence can be used in healthcare.
Used in business.
It can be used in education.
It can be used in autonomous vehicles.
AI can be used in robotics.

What Is Machine Learning?

Machine learning is a subset of artificial intelligence it is nothing but these are the study of computer algorithms that allows computer programs to improve automatically through the experience. Algorithms are a set of instructions in which a computer programmer specifies that a computer is able to process.

The main intention of machine learning is to make machines to learn by themselves by using given data and make accurate predictions. It is a technique to realize artificial intelligence. Machine learning trains the algorithms in such a way that they have to learn to take decisions.

Machine learning can be used in social media services.
It can be used in online customer support.
It can be used in online fraud detection.
Ml can be used in marketing and sales.
It can be also used in transportation.

What Is Deep Learning?

The subset of machine learning is deep learning. We can see deep learning is the next evolution of machine learning. The algorithms in deep learning are designed roughly by information processing patterns which will be found in the human brain. The algorithms of deep learning have taught me to accomplish the same tasks for the machine. Usually, the brain tries to decipher the formation of what it receives.

It can achieve this by labeling an assigning the items to various categories. You can understand the subtle differences between deep learning and machine learning by comparing them. Deep learning can discover the features which are to be used for classification automatically but you have to provide these features manually in the case of machine learning.

Comparison between Machine Learning, Artificial Intelligence, and Deep Learning

Artificial Intelligence

You may have heard of artificial applications or artificial engineers. So basically artificial intelligence enables computers or machines to think. That means without any human intervention the machine will be able to take its own decisions. Artificial intelligence will be the final goal. Let’s take an example self-driving car this is an artificial application.

Machine Learning

When we look towards machine learning as I mentioned above machine learning is a soft field of artificial intelligence, Which gives us some statistical tools to explore the data. When we’re talking about machine learning this machine learning has three types.

a. Supervised machine learning:

Supervised machine learning means we will be having some labelled data or some past data. By the help of this data, machines will be actually able to do the predictions for the future. Let’s take an example, we have some labelled data with colour and name of the fruit as our two features. Then we want to classify some fruits based on these two features.

What we have to do is we have to create a model and you have to train that model according to the data. And with the help of those data, we will be actually creating a supervised machine learning model. In supervised data, we will be knowing the output of this particular data.

b. Unsupervised machine learning:

In unsupervised machine learning, we will not be having any labeled data which basically means we will not be knowing output in our data set. So in unsupervised machine learning, we can easily solve the clustering type of problems like K means clustering, helical means clustering. When we say clustering what it exactly does is that based upon the similarity of the data it tries to group the data and there will be some mathematical concepts like euclidean distance Which will be actually used in the data.

So most probably we have three different algorithms here, those are K means clustering, helical means clustering, DBSCAN clustering. These are the three main algorithms that we use in unsupervised machine learning.

c. Reinforcement machine learning:

In the case of reinforcement machine learning, we will be provided with some parts of the data with labeled and some parts of the data will not be labeled. The machine learning model learns slowly by seeing the past data and it will be learning new data as soon as possible.

Deep Learning

If we look towards deep learning as I mentioned about deep learning is the subset of machine learning. The purpose of deep learning is to make machines to learn themselves as the human brain. This is the main idea behind deep learning. In deep learning, we have to create multi neural network architecture and we are trying to develop some deep neural network. The main intention of deep learning is to mimic the human brain. In deep learning also we are having various techniques or architectures,

a. Artificial neural network:

If the input/data which will be in the form of numbers, that can be solved by using artificial neural networks.

b. Convolutional neural network:

If the input/data is in the form of images, then that can be solved using a convolutional neural network.

c. Recurrent neural network:

If the input is in the form of time series kind of data then that can be solved by using recurrent neural networks.

I hope this article may help you all a lot. Thank you for reading. If you have any doubts related to this article “Difference between machine learning, artificial intelligence, and deep learning”, then comment below.

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