Artificial Intelligence vs Machine Learning: This is the Difference

Nowadays, many terms are thrown around interchangeably. You sometimes hear about Artificial Intelligence, but also about Machine Learning and perhaps even Deep Learning. This can make it quite unclear what exactly the term is that you are looking for and want to use. That is why in this blog we explain the difference between artificial intelligence and machine learning.

Simple Explanation of the Terms

Basically, we have already mentioned three terms in this article that can be quite unclear: Artificial Intelligence, Machine Learning and Deep Learning. We will briefly expand on what these three terms include:

• Artificial Intelligence: Artificial intelligence, also known as AI, is an umbrella term and science that deals with creating machines that exhibit certain intelligence.
• Machine Learning: Machine Learning, also known as ML, is a part of AI that focuses on techniques that allow computers to learn based on assumed data and patterns.
• Deep Learning: Deep Learning, also known as DL, is a part of Machine Learning that focuses on self-driving Machine Learning, where the algorithms make themselves leaner.

In short, Artificial Intelligence, Machine Learning and Deep Learning have a lot to do with each other and can be seen as categories and subcategories. They are always in relationship with each other. However, there is a lot of gray area, there are many intersections, algorithms and techniques.

Artificial Intelligence vs Machine Learning: What Exactly is the Difference?

Artificial Intelligence vs Machine Learning is explained quite simply. Machine Learning is part of Artificial Intelligence. A computer, which we now quickly call simple, is a form of AI. AI is a very broad term that covers all artificial intelligence.

Everything that exhibits (a form of) human intelligence and is made by humans can be seen as AI. One way to test whether something falls under AI is the Turning Test.

Machine Learning is a large and important part of AI. The basic principle of Machine Learning is that AI can learn based on input data and patterns. Machine Learning ensures that it is possible to extract relevant information from databases without a structured database.

We actually see Machine Learning everywhere these days. Just think of the recommended films from Netflix or the recommended products from Amazon. In short, the AI then learns the activities you have previously performed.

Deep Learning is one step further from Machine Learning. An AI can adjust itself. With Deep Learning, the AI can adapt to external data, while with Machine Learning this can only be done manually. The best example of Deep Learning is the self-driving car.

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