Importance of Deep Learning- How Deep Learning is Useful in Real-Time?
Deep Learning is a subset of Machine Learning & and is very counter intuitive in many cases. This blog is aimed at giving you in-depth knowledge of what exactly Deep Learning is, what makes it so crucial & what exactly are its use cases.
What is Deep Learning?
Deep Learning is an advanced concept in Artificial intelligence & is a subset of Machine Learning. The functioning of Deep Learning is based on Artificial Neural Networks with representation learning. The learning can be Supervised, Semi-Supervised, or Unsupervised Learning.
Artificial Neural Networks (ANNs):
Artificial Neural Networks (ANNs) are not just complex but are also a crucial part of Deep Learning systems. To help you get a clear understanding of how Artificial Neural Networks work, let’s compare their functioning with a human brain. The Human brain is made up of a network of neurons made up of nerve cells that possess the ability to collect and send signals to other neurons.
The functioning of ANN’s is quite similar to that of the functioning of neurons inside the human brain. ANN’s learn by analyzing data in several large volumes & come up with accurate outputs.
Differences between Machine Learning & Deep Learning:
As mentioned earlier, Deep Learning is a subset of Machine Learning however there are several differences between the two. One of the major differences between the two is the amount of data that is fed into the system. A Machine Learning system works better if we feed data in large volumes however there is a point of diminishing returns:
Deep Learning systems are capable of handling data in abundant volumes. As data is being generated at a rate that exceeds our expectations, the importance of Deep Learning is becoming more important & prevalent in the industries across the verticals.
The other major difference between Machine Learning and Deep Learning is the type of algorithms used. Machine Learning makes use of easy algorithms that lets you understand why a certain prediction occurred. On the other hand, Deep Learning makes use of several complex algorithms which makes it impossible to understand why a certain prediction has occurred. There’s no denying the fact that the predictions from Deep Learning systems are more accurate compared to Machine Learning systems.
Why Is Deep Learning Important?
As mentioned earlier, the Deep Learning system function better as more data is fed into it, it also thrives with specific use cases. However, it doesn’t mean that you can find the solution to any problem by feeding a Deep Learning system with relevant data, it has its limitations just like Artificial Intelligence & Machine Learning systems. In certain use cases, we can observe Machine Learning Algorithms outperforming Deep Learning Algorithms.
The applications of Deep Learning have become crucial in many areas like Natural Language Processing (NLP), Computer Vision, Pattern Recognition, and more.
The smart digital assistants which we use in our daily life Alexa, Siri, and other voice applications are powered by Natural Language Processing. These devices are capable of converting voice commands into text. The algorithm would be then analyzing the entire dictionaries of words and creates sentiment from these words to deliver users relevant responses. With the advent of Deep Learning, the advancements in NLP are happening at a rapid pace.
Deep Learning has the ability to process large volumes of data volumes & is very powerful when it comes to handling large sets of unstructured data. However, the use of Deep Learning algorithms may show adverse affects when you are dealing with data of less volume. One thing is for sure that, over the coming years, the advancements in Deep Learning would be impacting enterprises across the industry verticals at large.
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