A BRIEF INSIGHTS ON DIFFERENCE BETWEEN AI VS ML VS DEEP LEARNING
Very often we confuse ourself between the terms machine learning, AI and deep learning and often used them interchangeably. without researching about in a depth about the keywords, we land up in great confusion.
so, today my article is on what is the difference between these all three
AI is a broader concept then ML, which addresses the use of computers to copy the cognitive functions of humans. when machine carries out the task based on algorithms in an intelligent manner, that is AI.
Machine learning is a subset of AI and focuses on the ability of the machine to receive a set of data and learn for themselves, changing algorithms as they learn more about the information they are processing.
Training computers to think like the human is achieved partly through the use of neural networks. neural networks are a series of algorithms modelled after the human brain.
just as the brain can recognize the pattern and help us categorize and classify information, neural networks do the same for computers.
Shown here is the diagram where i can explain you in a better way
so deep learning is a subset of machine learning which in turn machine learning is a subset of AI as shown in the given diagram.
The brain is constantly trying to make sense of the information it is trying to do this, it labels and assigns items to categories. When we encounter something new, we try to compare it to a known item
to categories. When we encounter something new, we try to compare it to a known item to help us understand and make sense of it. neural networks do the same for computers.
1- Extract meaning from complicated data.
2- Detect trends and identify patterns too complex for the human to notice.
3- learn by example.
4- speed advantage.
Deep learning goes yet another level deeper and can be considered as a subset of machine learning.
The concept of deep learning is sometimes just referred to as deep neural network referring to the many layers involved. A neural network may only have a single layer of data, while a deep neural network has two or more. The layers can be seen as a nested Hierarchy of related concepts or decision trees.
Deep learning network needs to see large quantities of items in order to be trained.
Instead of being programmed with the edges that define items, the system learns from exposure to millions of the data points.
CONCLUSION
so, today my article is on what is the difference between these all three
AI is a broader concept then ML, which addresses the use of computers to copy the cognitive functions of humans. when machine carries out the task based on algorithms in an intelligent manner, that is AI.
Machine learning is a subset of AI and focuses on the ability of the machine to receive a set of data and learn for themselves, changing algorithms as they learn more about the information they are processing.
Training computers to think like the human is achieved partly through the use of neural networks. neural networks are a series of algorithms modelled after the human brain.
just as the brain can recognize the pattern and help us categorize and classify information, neural networks do the same for computers.
Shown here is the diagram where i can explain you in a better way
so deep learning is a subset of machine learning which in turn machine learning is a subset of AI as shown in the given diagram.
The brain is constantly trying to make sense of the information it is trying to do this, it labels and assigns items to categories. When we encounter something new, we try to compare it to a known item
to categories. When we encounter something new, we try to compare it to a known item to help us understand and make sense of it. neural networks do the same for computers.
Benefits of neural networks
1- Extract meaning from complicated data.
2- Detect trends and identify patterns too complex for the human to notice.
3- learn by example.
4- speed advantage.
Deep learning goes yet another level deeper and can be considered as a subset of machine learning.
The concept of deep learning is sometimes just referred to as deep neural network referring to the many layers involved. A neural network may only have a single layer of data, while a deep neural network has two or more. The layers can be seen as a nested Hierarchy of related concepts or decision trees.
Deep learning network needs to see large quantities of items in order to be trained.
Instead of being programmed with the edges that define items, the system learns from exposure to millions of the data points.
CONCLUSION
- algorithms which are created by human programmers which are responsible for passing and learning from the data is what we call machine learning. The computers based on ML makes a decision based on what they learn from the data.
- On the other hand deep learning learns through an artificial neural network that acts very much like the human brain and allows the machine to analyze data in a pattern very much as human do. These machine based on deep learning don't require a human programmer to tell them what to do with data.
HAPPY READING!!!!
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