Аrtificial Intelligence vs Machine Learning vs Deep Learning – these are three very hot buzzwords at the moment, which often seem interchangeable, but they are actually very different.
For the purposes of this thought piece, we will use not only the context of how we simulate human intelligence, but also how we gradually build upon one another. I will first give you a brief overview of what machine learning and artificial intelligence really mean and how they differ. What I present here will remain relevant for a while, so I will start by giving you some background on what they actually mean and some examples of how each of them work.
Artificial vs. Machine Learning: Main Differences
Artificial intelligence (AI) comes from computer science, while machine learning (ML) is a subset of artificial intelligence.
But here’s where things get tricky – In addition, machine learning is another subset of artificial intelligence. However, it covers all aspects of the cognitive behavior of an artificial system. So, to break it down into a single sentence: Deep learning processes are specialized subclasses of machine learning, which in turn are subordinated to artificial intelligence.
or in other words…
We use Machine Learning to develop Artificial Intelligence.
What is AI but is not Machine Learning?
We have Machine Learning when the system is learning by itself. It does that by using statistical methods, analysis and data.
always keep that in mind when you are trying to find the differences.
How is Machine Learning use and where is it implemented?
Machine learning is implemented using deep learning techniques such as deep neural networks ( and neural network algorithms). Machine learning can also be implemented or imitated with DL-based systems and deep learning processes.
Machine learning has been used in the field of computer science for many years with various types of deep learning methods and techniques.
How are Machine Learning and Artificial Intelligence similar?
Machine learning and artificial intelligence are both based on algorithms, but they differ depending on whether the data they receive is structured or unstructured.
How are Machine Learning and Artificial Intelligence different?
So, AI and ML differ in the type of data they receive, the number of inputs and outputs, and the amount of computing power needed for the specific project.
Although they share common characteristics, we can see that they are different technologies. Both, as you can see, have greater potential. They are located within the data technology ecosystem and are currently reaching a highly improved level of development.
Are Deep Learning and Machine Learning the same?
Let us go a little deeper to understand what the difference is between machine learning and deep learning in general and artificial intelligence in particular.
Now read carefully: Although everything that is categorized as “deep learning” or “machine learning” is part of the field of artificial intelligence, not everything that is “machine learning” will be “deep learning.”
So, to provide your companies with machine learning and deep learning systems, you need a way to make engineers from both tech fields work together.
Machine Learning includes Deep Learning.
Working with AI vs. Working with ML
One thing is certain: whether you use an artificial intelligence algorithm or machine learning, if the data used is incorrect, the knowledge and information obtained will be incorrect. Whether you choose machine learning or deep learning, you can work on improving your artificial intelligence.
In conclusion, although both terms (AI and ML) are often used interchangeably, they are not the same. The reason behind this article is to clear up the confusion between Artificial Intelligence, Machine Learning and Deep Learning – the terms comprehensively – in order to understand them.