Data Science

Difference – Artificial Intelligence & Machine Learning

In this post, you learn the difference between artificial intelligence & machine learning.

Artificial intelligence represents a set of computer programs that imitate human intelligence.

The diagram below represents the key difference between AI and Machine Learning. Basically, machine learning is a part of AI landscape. One can do AI without doing machine learning or deep learning. Thus, an organization can claim that they have AI-based systems without having machine learning or deep learning based systems. 

All machine learning or deep learning based systems can be termed as AI systems. But, all AI systems may not be termed as machine learning systems.

Fig 1. Difference between Artificial Intelligence & Machine Learning

The following are key building blocks of an AI-based system:

  • Large set of complex rules: Computer programs representing application comprising large set of complex rules which could imitate human intelligence. These rules are created by the developers. Those creating such AI programs could be developers.
  • Machine Learning: Computer programs representing mathematical model (s) / function (s) where the coefficients / parameters of the mathematical model is learnt from the training data (past experience). The features  of machine learning models are hand-crafted by the data scientists.  Those creating machine learning models are data scientists or ML engineers. The coefficients / parameters of machine learning models / programs are learnt based on optimization algorithm.
  • Deep Learning: Deep learning represents a class of machine learning models / programs which imitates human neural network. In other words, deep learning can be said to be a subfield of machine learning. In deep learning models / programs, the features are learnt automatically based on the optimization algorithm. The word, “deep” in deep learning is about learning successive layers of meaningful representations of data. Those creating such models are termed as Deep Learning practitioners. the diagram below represents layers of representations for data (face).

    Fig 2. Deep Learning – Learning Layers of Representations

One may also ask if AI is related with the field of Data Science. 

Data Science is a field of IT which comprises field of mathematics and Statistics along with machine learning to train the model.  

Ajitesh Kumar

I have been recently working in the area of Data analytics including Data Science and Machine Learning / Deep Learning. I am also passionate about different technologies including programming languages such as Java/JEE, Javascript, Python, R, Julia, etc, and technologies such as Blockchain, mobile computing, cloud-native technologies, application security, cloud computing platforms, big data, etc. I would love to connect with you on Linkedin. Check out my latest book titled as First Principles Thinking: Building winning products using first principles thinking.

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