Machine Learning, AI, Deep Learning and Data Science are very closely related areas of study and most people often confuse them to be the same. However, there is a significant difference between the 4 and understanding them is very important if you want to build a career in the field of Data science.
Let’s see the difference between Machine Learning vs. AI vs. Deep Learning vs. Data Science!

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To put it simply, Deep Learning is a subset of Machine Learning which in turn is a subset of AI. On the other hand, Data Science is a different field which includes AI, Machine Learning as well as Deep Learning.

Artificial Intelligence
It is a field of science in which machines are made to demonstrate human like intelligence, also called Artificial Intelligence, with the help of various codes, algorithms or techniques.

Machine Learning
As mentioned earlier, Machine Learning is a subset of AI. The computers are made to learn tons of algorithms and statistics which helps them perform tasks without the help of human interference.

Deep Learning
Deep Learning is a part of Machine Learning. With the help of Machine Learning, computers solve problems based on algorithms they are fed. However, Deep Learning allows computer to further identify patterns and distinguish objects, giving them a more human like intelligence. Deep Learning is based roughly on the functionality of the human brain. It distinguishes objects and deciphers data which is then used by Machine Learning to perform tasks.

Data Science
Data Science is used to analyses data in order to derive actionable information. It is used by machines for decision making and problem solving purpose as it analysis data and builds algorithms which the machine can work upon.
It makes use of AI, Machine Learning, Deep Learning as well as other statistical and analytical tools to analyze and manipulate data.

Conclusion
AI makes machines exhibit human like intelligence. Machine Learning allows machines to perform tasks with the help of pre-fed data and algorithms. Deep learning makes machines capable of identifying, distinguishing and classifying patterns and objects.