Updated: Feb 10, 2020
The common question for the beginners in the machine learning community, uphold your eyebrows if you have this question in mind – What is the difference between AI vs Machine Learning Vs Deep Learning?
Let’s see a picture together.
I am pretty sure after seeing this image, you got a rough idea that Deep Learning is a subset of Machine Learning and Machine Learning is a subset of Artificial Intelligence.
Let's deep dive in some definitions:
It is nothing but a simulation of the human mind. The way human comprehends the real world situation and deal with the tough problems in that same way AI technology is helping machines to copy humans and produce results lightning fast and without a single error.
Machine Learning is a technique by which we(humans) are teaching machines to do certain types of work on its own. Now, the main question arises, how are we doing this?
For example, how do we classify 3 different colored balls?
Answer: you still thinking… It’s by the color feature, Right?
In that same way, we have an AI technique named clustering(grouping) in which the data is plotted on coordinates and the machine observes how near one color is from another(from a euclidian distance) and for the nearer the colors the same colored clusters will be made.
Machine Learning contains several classifications. The general level classifications are:
3 of the above mentioned classes carries several techniques:-
Support Vector Machine(SVM)
Artificial Neural Network(ANN)
Naive Bayes Theorem
Unsupervised Learning :
Deep learning is a sub part of machine learning which is powered by Artificial Neural Network(ANN). ANNs are computing systems vaguely inspired by the biological neural networks that constitute animal brains. Deep learning constitutes a deep neural network i.e. Neural network with a large number of hidden layers.
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