If you are interested in artificial intelligence, you have probably heard the terms machine learning (machine learning) and deep learning (deep learning) and you must have wondered what is the difference between the two? In this article we are going to talk about the difference between machine learning and deep learning.
What is machine learning?
Machine Learning is a subset of artificial intelligence, thanks to which we can have systems that learn and develop automatically and without explicit planning. Machine learning essentially focuses on the development of computer programs that can access and learn data on their own. (For more information on this, see What is machine learning and what does it do? )
What is deep learning?
Deep learning is actually machine learning, but in a deeper and more advanced form, so that its function is more similar to the function of the human brain. Deep learning uses a programmable neural network that helps the machine make more accurate decisions without human help. In other words, if machine learning mimics the human type of learning, how to mimic the human brain is the same idea behind neural networks.
In fact, deep learning is a type of machine learning algorithm that receives raw input and extracts high-level features in several layers.
In fact, deep learning is part of a larger family of machine learning that focuses on methods based on artificial neural networks (algorithms that simulate the functioning of the human brain).
The difference between deep learning and machine learning
We have to say that deep learning is actually an evolution of machine learning that has far more depth than machine learning. The data used in deep learning is far more than machine learning, and we will actually be working with Bigdata. As a result, computing in Deep Learning becomes much more complex, resulting in more powerful hardware such as a graphics card. This hardware is usually located in data centers and with the help of creating artificial neural networks, the processing power required by the program is provided.
One of the differences between deep learning algorithms and machine learning algorithms is the issue of problem segmentation. In fact, in machine learning algorithms, the problem is divided into smaller parts and then solved, but in deep learning, the problem must be solved in its entirety without breaking into smaller parts. Therefore, the amount of data required for deep learning is much more than machine learning and as a result, the time required will be more.
Another difference between machine learning and deep learning is the way you look at it. In fact, in-depth learning does not begin with pre-determined information, and the program uses much more detail to learn. Hence, the time required for the program to learn will be much longer than the learning machine.
Deep learning applications
Among the applications of deep learning, we can use automated machines, fake news detection, natural language processing, virtual assistants, visual detection, fraud detection, health, and so on.