Both deep learning and machine learning have created a huge impact in a myriad of sectors, including both industry and academics. Their abilities have played and continue to play a significant role in shaping the industry. While the AI world is growing faster than the speed of light, it is not always easy to keep up with the latest AI world updates. However, in case you wish to understand at least the basics, then the two concepts, deep learning, and machine learning, are perhaps the very first things you should be studying. Moreover, the importance of carefully understanding the difference between the two is also a must.
Here are the differences that one needs to know between the two in order to eliminate almost all confusion.
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How is machine learning different from deep learning? Let’s find out!
Before understanding the differences, it is essential to first understand the meaning. After all, their separate meanings would tell us how the two are essentially different from each other.
Beginning with deep learning, can be said that it is an artificial intelligence concept that mimics how the human brain functions in processing data and developing patterns for the purpose of making decisions.
On the contrary, machine learning is an artificial intelligence technology that automatically makes it possible for systems to learn and develop through experiences sans the need of getting programmed explicitly.
Okay, so what are generally the objectives of each of them?
Deep learning is a form of artificial intelligence that learns sans being managed from unlabeled data. Therefore, it can be called deep neural learning as well.
On the other hand, the objective of machine learning is the growth of software programs that can make use of knowledge to comprehend for themselves.
How do the hardware needs make them different?
Machine learning is possible in comparatively less powerful hardware than deep learning. The reason why deep learning needs stronger hardware is because it has neural networks in multiple layers. This requirement can play the role of a barricade for organizations who wished to enter sans the needed hardware needs.
Finally, how do they differ in complexity?
Well, machine learning needs less data as compared to deep learning, and thus less complex models are required in the former. Therefore, organizations having limited data resources may face difficulties with deep learning.
The takeaway
While deep learning and machine learning are often seen as the same, they are very different from each other. However, both play a significant role in shaping the AI world. While the AI world is actually not new to mankind, the significant rise of the AI world is something that humans weren’t expecting. Therefore, to get comfortable with the emerging changes and advancements, it is important to first clarify the very basics. Understanding the difference between machine learning and deep learning comes under the ambit of these fundamental aspects.
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Categories: Trends
Source: vcmp.edu.vn