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Deep Learning

Hierarchical learning or deep structured learning is a subfield of machine learning. It can be in a supervised, semi-supervised or unsupervised manner. Deep learning has gained momentum in the last few years and was used to solve numerous problems which ranged from natural language processing to computer vision. Currently, deep learning is used heavily to build intelligent systems with the purpose of assisting humans in several activities. Problems which seemed unsolvable can now be easily solved with the help of deep learning. Deep learning is so named because of the numerous layers which the data has to go through for processing.

Over the last few years, several major breakthroughs in data science was a result of deep learning. Moreover, deep planning applications are slated to see a rise in demand in the future because of their ability to increase the cognitive skills of Artificial Intelligence. Several companies are trying to develop deep learning applications to be used in various feels such as in the military, cybersecurity, customer service, data analysis, robotics, and many others.

Areas of Deep Learning

Deep learning is a rapidly developing concept which helps the Artificial Intelligence to increase its accuracy while performing tasks that require cognitive abilities. Some of the areas where Deep Learning is used are:

 

In Conclusion

The ability of deep learning to recognize patterns and learn from them is what makes it more adaptable to various situations. It is even helping people to solve problems which were not thought to be possible without human input. Through deep learning, a new generation of Artificial Intelligence is coming into being that has the ability to make decisions on its own.

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