Why is Deep Learning So Popular? Benefits & Applications of Deep Learning
The prominence of Artificial Intelligence and its related technologies is exponentially growing in recent years especially Deep Learning and Neural Networks. Most of the tech experts are of the option that Deep Learning would be the next generation of computing in the. Strengthening this statement, three researchers have been presented with Turing Award, for their extensive research on Deep Learning. For those who aren’t aware of Turing award let us tell you that it is Computer Science’s award equivalent of the Nobel Prize.
Now, let’s understand what exactly is Deep Learning & why is it gaining such a huge popularity.
What Is Deep Learning?
Deep Learning is a part of Artificial Intelligence and is a subset of Machine Learning. Deep Learning is far more advanced concept than Machine Learning & it has numerous advantages.
If you are aware of Machine Learning then you much know that this technology is all about pattern recognition. If a computer system is trained to recognize patterns in a given domain then, it would be easily classifying the data by relying on its learning from past trials. When it comes to Deep Learning, it is much superior to Machine Learning and is an end-to-end problem solver.
Deep Learning models rely on the chain of neural networks that are made up of neural nodes that trains themselves over time through reinforcement. Understanding how exactly Deep Learning algorithms function would be very difficult.
Benefits of Deep Learning:
- Unlike Machine Learning, Deep Learning models perform feature extraction and classification in one shot. So, rather than building two different models, these two tasks can be executed parallel by building on one model.
- Deep Learning models are literally capable of processing data in sheer volumes at high processing speed using GPUs.
- Deep networks models are capable learning highly complex features by using the back-propagation algorithm.
- There several open source libraries like Keras, Pytorch, and TensorFlow using which we can easily build a Deep Learning model.
Smart Applications of Deep Learning:
Face & Object Recognition
Most of the advanced computer vision applications that are currently in use like Self-Driving cars, Facial Unlock feature in our smart phones, etc are powered by Deep Learning technology. Deep Learning powered Image Recognition applications are so powerful that few tech-driven companies use it to estimate damage after disasters just by making the model analyze the images.
Natural Language & Speech
Most of the prominent voice command applications that we use in our smart phones & house hold appliances like Google Assistant, Apple’s Siri, Amazon Alexa etc rely on Natural Language which is the application of Deep Learning. Most of AI powered language translators that we find online are powered by Deep Learning’s NLP & Speech Recognition applications.
If you are willing to perform pattern recognition then there’s no other technology better than Deep Learning for this job. Most of the tech-driven enterprises rely on Deep Neural networks to detect fraud in real time based on behavioural analysis and statistics about past fraudulent transactions. Most of the social medial platforms use Deep Learning to detect fake user accounts.
Deep Learning has improved data processing models and it can generate precise results when it comes to handing complex Data Science tasks. As we are clearly aware of the fact that Machine Learning is apt when it comes to handling labelled data, in contrast Deep Learning supports unsupervised learning techniques & this enable the systems become more sophisticated and smarter without much of human intervention.
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