You might have heard about the terms Deep learning, and Machine learning a thousand times(even if you are not somehow connected to the world of Data Science). They certainly have become some of the buzzwords in today’s technological world. These things have become popular over these years, and while they are going to stay, many people are confused between what is Artificial Intelligence, what is Machine learning, what is Deep learning, and there are a ton of other confusions.
Understanding this, we have come up with this easy-to-understand article, in which, we are going to learn about what is Deep Learning, what is Machine learning, and then we will also have a look at some of the points of differences between Deep learning, and Machine learning.
In broader terms, we can simply mention that Deep learning is a subset of Machine learning, and Machine learning is a subset of Artificial Intelligence. This is like AI seems to be the largest bubble, which carries Machine learning, and in turn, Machine learning is again a bubble, carrying Deep learning.
Deep Learning vs Machine Learning
In this article, we are going to understand about the terms Deep learning and Machine learning, and we will understand some points of differences, so that next time you use these terms or explore them, you can just keep away the confusion, and all the instabilities in your software.
What is Machine learning?
If we were to explain Artificial Intelligence in easy-to-digest terms, it would state that – Artificial Intelligence enables the creation of systems, which can simulate human cognitive functions, and perform tasks, which usually require human intelligence.
Well, Machine learning is a subset of this Artificial Intelligence, and Deep Learning, in turn, is a subset of Machine learning. But what is Machine learning?
Machine learning enables the machines to learn from the experience, and make some predictions, or take decisions, without being explicitly programmed.
For example, just imagine that there is a kid, and we show a lot of images of dogs, specifying that it is a dog, and other images specifying that it is not a dog. After showing a few images, if you show some unseen image to the kid, it can easily specify whether it is a dog or not a dog.
We can say that we are training the kid, to classify between a dog, and not a dog, when it is shown a new image. Just like this, we can train the machine, feeding it a lot of data. The machine follows some rules to analyze and draw conclusions from the data.
Even today, Machine learning is in action in many different areas, from entertainment to security. It is helping humans in many terms, making their lives easier.
Well, we have earlier mentioned that Deep learning is a subset of Machine learning. So, now we know in super brief about what is Machine learning, and it takes us to further discussion, on what is Deep learning.
What is Deep learning?
Deep learning draws its inspiration from the structure and function of the human brain. The human brain has something called a neuron, which you can explore, but simply we can understand the neurons as fundamental units of the brain and nervous system.
Deep learning involves training the Artificial Neural Networks, to learn from the data. It mimics the learning process of the human brain.
When we are working on Machine learning algorithms in general, we are working on relatively smaller data sets, and also in general, we need to specify the features.
On the other hand, with Deep learning algorithms, we can work on big data sets(and unstructured data too), and also, we do not need to specify the features, since the features are learned automatically.
The thing is that Deep learning also requires comparatively higher computing power, but thanks to the advancing GPUs and other technologies, the training time for deep learning algorithms is much reduced(but still it may need hours, if not days).
We can say that Deep learning is a type of Machine learning, but not all Machine learning is Deep learning. If you are interested in exploring more about Deep learning, you can certainly explore, since there is a lot to discuss.
Now, let’s move towards discussing some points of differences between Deep Learning, and Machine learning.
Difference between Deep Learning and Machine learning
Deep learning | Machine learning |
---|---|
Involves training Artificial Neural Networks to learn from the data(actually a huge amount of data). It mimics the learning process of the human brain. | Enables machines to learn from experience, and take decisions, or make predictions, without being explicitly programmed. |
Deep learning is a subset of Machine learning | Machine learning is a superset of Deep Learning. |
When working with Deep learning algorithms in general, we need relatively bigger datasets. | When working with Machine learning Algorithms in general, we work on relatively smaller datasets. |
While working with Deep learning algorithms in general, we need high computation power. So, some high-end machines might be required to carry out the operations, or at least optimize the time required for operations. | While working with machine learning algorithms in general, we can work on quite low-end machines. Comparatively less computational power is required. |
In deep learning, the features are automatically learned. | In Machine learning, we are required to specify the features. |
Deep learning algorithms generally take more time for training. | Machine learning algorithms take less time in training. |
Deep learning models perform better on huge datasets. | Machine learning algorithms can perform well on smaller or medium datasets as well. |
In Deep learning, the general goal is to mimic the process of the human brain. So here, we have a neural network(artificial). | In Machine learning in general, the goal is to get closer to the actual output. |
Applications of Deep learning include Natural Language Processing, Speech Recognition, Computer Vision, Image processing, etc. | Applications of Machine learning include Recommendation systems, Fraud Detection, etc. |
Conclusion
In this article, we tried to discuss what is Deep learning and what is Machine learning, and we discussed some points of differences between Deep learning and Machine learning. Artificial Intelligence, Machine learning, and Deep learning are becoming increasingly popular these days, and they are here to stay and help humans in many terms.
If you wish, you can explore these fields more, since it is an ocean, of concepts, and of opportunities. You can explore Machine learning, Python, and much more, and have a career in Machine learning, Data Science.
FAQs related to Deep Learning vs Machine learning
Q: What is Machine learning?
Ans: We can understand machine learning as something, which enables the machines to learn from the data, make predictions, and take decisions, without being explicitly programmed. This is like we are feeding a lot of data to the machine, from which is learning, and then acting accordingly.
Q: What is Deep learning?
Ans: Deep learning is a subset of Machine learning. It involves training the artificial neural networks to learn from the data. It mimics the learning process of the human brain.
Q: Is Deep learning a subset of Machine learning?
Ans: Yes, Deep learning is a subset of Machine learning.
Q: What is Artificial Intelligence?
Ans: Artificial Intelligence can be considered as creating systems, which can simulate human cognitive functions, and perform tasks, which require human intelligence, like decision-making, object recognition, speech recognition, etc.