Blog: What is the Difference between Artificial Intelligence (AI), Machine Learning (ML) and Data Science
Today Modern technologies like artificial intelligence, machine learning, data science have become the buzzwords. Everybody talks about but no one fully understands. They seem very complex to a layman. People often get confused by words like AI, ML and data science. In this article, we explain these technologies in simple words so that you can easily understand the difference between them.
“AI is the New Electricity”
Artificial Intelligence is a very wide term with respect to its application in the real world, but basically, Artificial Intelligence means “making machines intelligent”, so they can take some decisions on there own according to the situations without the need of any human interference. And Machine Learning is “the way to make those machines intelligent”.Machine learning is a subset of AI that focuses on a narrow range of activities. Data science isn’t exactly a subset of machine learning but it “uses ML to analyze data and make predictions about the future”. It combines Machine Learning with other disciplines like big data analytics and cloud computing to solve real-world problems.
Deep Dive into these Technologies
What is Artificial Intelligence?
Artificial intelligence refers to the simulation of human brain activities by machines. It is a discipline where we make a machine try to analyze the situations and make an inference out of it.
Artificial intelligence is classified into two parts, general AI and Narrow AI. General AI refers to making machines intelligent in a wide array of activities that involve thinking and reasoning. Narrow AI, on the other hand, involves the use of artificial intelligence for a very specific task. For instance, general AI would mean an algorithm that is capable of playing all kinds of board game while narrow AI will limit the range of machine capabilities to a specific game like chess or scrabble.
What is Machine Learning?
Machine learning is the ability of a computer system to learn from the environment and improve itself from experience without the need for any explicit programming. Machine learning focuses on enabling algorithms to learn from the data provided, gather insights and make predictions on previously unanalyzed data using the information gathered. The three basic models of machine learning are supervised, unsupervised and reinforcement learning.
What is Data Science?
Data science is the extraction of relevant insights from data. It uses various techniques from many fields like mathematics, machine learning, computer programming, statistical modelling, data engineering and visualization, pattern recognition and learning, uncertainty modelling, data warehousing, and cloud computing.