What is the difference between Machine Learning and Artificial Intelligence?

People always get confused as to what is the basic difference between Machine Learning and Artificial Intelligence. Some consider both of them as one. I did complete research and found the answer. Artificial Intelligence is a vast subject and we can say Machine Learning is a subset of it. It doesn’t end here, there is a lot more to this. You can find it on Turingtribe website and please share your thoughts and your suggestions. If you have anything more to share about AI, ML and Data Science please share! I am an absolute AI Brat :sweat_smile:


yeah man you are right

Artificial Intelligence is the study of how to train the computers so that computers can do things which at present human can do better, while Machine learning refers to learn from experience while performing some task and having some performance measure.

AI doesn’t exist cause we can’t create an intelligence we even don’t know what it is. Computer can’t think so how can he be intelligent but ML, Deep Learning is interesting techniques

I think the main difference between Machine Learning and Artificial Intelligence is that AI, first of all, means that the computer imitates human behavior, and Machine Learning is a part of AI which consists of methods that allow computers to draw conclusions from data and provide them to AI applications. You can learn more about difference between Machine Learning vs AI vs Data Science: https://www.cleveroad.com/blog/data-science-vs-machine-learning-vs-ai

There’s a joke amongst ML/AI folk:

It’s Machine Learning if it’s written in Python.

It’s Artificial Intelligence if it’s written in PowerPoint!


Coursera’s AI for Everyone is a great course to learn a lot more about AI.

There is another great free course on AI called the “Elements of AI” that answers this question directly. Here is the lesson page on this topic: Related Fields (to AI)

And here is the course link, I am on Chapter 3 myself: Elements of AI

The difference between AI & Machine Learning

  1. Main aim of AI is to increase the chances of success but no accuracy but on the other hand ML focuses on accuracy rather than success.
  2. AI goal is to stimulate natural intelligence to solve complex problems but the goal of ML is to learn from data for a certain task to maximize the performance of the machine.
  3. Primarily AI is used for decision making but ML allows the system to learn from the previous experience.
  4. AI develops a system to mimic humans, thus the system can respond and behave in certain circumstances but ML helps in self-learning algorithms.

Read Here: Machine Learning vs Artificial Intelligence

Machine Learning usually refers to some kind of tools for computational problem solving. The word “Learning” is used because relevant data collected about the target phenomenon is injected into the algorithm in order to produce a model. The parameters of the model are found by “learning” from the data. Those procedures might or might not be heuristics. Results are usually empirical (ie. the model and its parameters are not generalizable beyond the data in use). The most recent trend is to open the blackbox of the heuristics.

AI is more a concept, and you use ML as one of the tools to realize that goal. The ideal goal that a person working on AI is committed to is to accomplish a machine that pass the Turing Test. Machines can be considered closer to beating the test in some degree, although that can be subjective.

Not all the applications of ML algorithms are to accomplish AI. Similarly, not all the algortihms used for AI have been ML based, although today they are the most used.