The differences or rather co-relations between machine learning, deep learning and AI.

In today's era we are most familiar with these terms machine learning(ML), deep learning(DL) and artificial intelligence(AI). And we are always confused that what exactly these terms are. So, I have tried to answer this in a very layman way which can be understood by anyone.

The co-relations between machine learning, deep learning and AI.

Artificial intelligence(AI) - It is the ability of a computer program or a machine to think and learn or in simple terms act like human, it is a very layman definition. And in context of this article AI is broader field and this can be implemented in various ways and machine learning is one of the way of doing that. So, In this context AI is a broader field.

Machine learning(ML) - Now, the AI programs that run that learn from past data or experience without being explicitly programmed is termed as machine learning. So, in this context machine learning can be interpreted as the sub-set of Artificial Intelligence. Quantitatively, machine learning is applied to a data set of the order of thousands.

Deep learning(DL) - And the ML or machine learning programs or models which were inspired by the working of active neurons in human body is basically termed as deep learning, this can be a very layman way to explain the co-relations and differences to many. These models have various layers in them and they are an input layer, a set of hidden layers and an output layer in there architecture. These models are applied to data sets having data of the higher order than ML.

So, here I have tried to explain this in a very layman way. Please, do share this, if you like it. Do subscribe to my website because, I will be having more blogs related to artificial intelligence, so you never miss them.