AI VS Machine VS Deep Learning

The confusion:

These terms can be confusing for many people but in clear terms

  • Deep Learning is a Subset of Machine Learning
  • And Machine Learning is a Subset of Artificial Intelligence

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Let’s start from

Artificial Intelligence:

The term artificial intelligence came into existence and the term AI first coined in 1956. But it becomes popular recently. Previously we had very little amount of data. Those were insufficient to predict. It is suggested that by 2020 the accumulated volume of data will increase from 4.4 ZB to 44 ZB! Along with amount data we also now have large amount of storage capacity and high end computational power.

What does that mean?

Studies show that the 70% of enterprise will adopt the AI within next 12 months.

So what is Artificial Intelligence?

Artificial intelligence is a technique which enables to mimic human behavior. Ex Mechina?
It is possible for the machine to learn from the experience. Artificial intelligence can be trained towards achieving set of goals by processing large amount of data and by recognizing pattern in them.

How machine learning came into the picture.

Machine learning first appeared in between late 80s and early 90s.

But why?

Machine learning is a subset of AI technique which use statistical methods to enable machine to improve with experience. These algorithm are designed in a way which can learn overtime to improve from new data.

Deep learning

Deep learning is a particular kind of machine learning that is inspired by the functionality of our brain cells called neurons which led to concept of artificial neural network. YOU CAN CALL IT A BLACK BOX.

Machine Learning VS deep learning

Deep learning is machine learning. Can say that it is the next evolution of Machine learning. But machine learning works with smaller amount of data but in order to work well with Deep learning, it needs very large amount of data.

Hardware Dependency

Machine learning can work with average computer but deep learning require high end machine configurations. Deep learning uses GPU which is a vital part of the algorithm. This use large number of matrix multiplication operations.

Feature Engineering

This is process of putting the domain knowledge to reduce the complexity and make patterns more visible to learning algorithm. This is difficult in terms of time and expertise. This patterns need to be identified by the expert then need to hand codded.

Learning time:
Deep learning takes longer than machine learning.
Execution time:
Deep learning takes leaser than machine learning.
When choosing deep learning, it is thought several times because the final out through deep learning has no explanation at the other hand when a decision has taken using machine learning it has the explanation of its consequence.


  • Machine learning uses algorithm to parse data, learn from that data, and make informed decisions based on learning
  • Deep learning structures algorithm in layers to create an artificial “neural network” that can learn and make intelligent decisions on its own.
  • Deep learning is a sub field of machine learning. While both fall under broad category of artificial intelligence, deep is usually what is behind the most human like artificial intelligence.

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