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Introduction to deep learning
Introduction to deep learning

What is deep learning?

Deep learning can be defined as a field of artificial intelligence that deals with machines. It is concerned with the task that mainly requires human intelligence. This is mainly where the machines can learn several tasks and do them without any kind of human involvement. Deep learning can be defined as a subset of machine learning. It mainly uses artificial intelligence to acquire some skills without any kind of involvement from humans. The reason that this is termed deep learning is that the neural network has many layers.

8 examples of deep learning:

  • Virtual assistant: 

The virtual assistant is a form of robotic automation at the highest level. It identifies data from multiple sources and places it in context, learning from each interaction. By using advanced language processing techniques, a virtual assistant can be able to analyze everything said or typed and formulate a correct response. Advanced virtual assistants are able to handle multiple tasks and complex inquiries through the use of artificial intelligence and machine learning. By analyzing previous choices and data, they are able to gain insight into one’s preferences.

  • Translations:

It has helped in many ways and one of the ways that it has helped is through translating between languages. This is very useful for the people who love to travel or business people and also for the people in the government. This aspect of deep learning helps to combat the language barrier that people used to face in the past. 

  • Visions for the driverless delivery trucks, drones, and autonomous cars:

Some vehicles are now being designed to understand the realities of the road and respond to several things such as the ball on the street, stop signs, and many other things. These things are only possible through the help of deep learning. The algorithms help to better understand the road and everything. The more information that they have, the better they can respond to different situations. 

  • Service bots and chatbot:

Chatbot and service bots are taking over many industries by providing the customers with a unique way of providing customer services through analyzing their moods etc.

  • Facial recognition:

Smartphones have this feature that allows them to unlock only when they recognize the owner. This is classified under biometric security. An example of biometric software is voice recognition, fingerprint recognition, and ocular retinal or iris identification.

  • Image colorization:

Human hands mainly carried out the task of image colorization, which is transferring black and white images into color, and with the changes in technology. This helps to recreate the black and white images into colored ones and the results are outstanding. 

  • Pharmaceuticals and medicines:

Humans have faced several diseases in the past and it is evident that deep learning has helped to design medicines according to the needs of the patients. This is based on medicines created after reading individuals’ gnomes. 

  • Shopping and entertainment experiences being personalized:

The deep learning algorithms have changed the shopping and entertainment experiences. Have you ever wondered how are you getting ads for the things that you talked about or just searched? Alternatively, Netflix gives suggestions regarding a show that you might like. The behavioral and transactional data in order to build an understanding of the customer’s needs. As a result of collecting and processing data, e-commerce companies can recommend customized products to customers in real time and therefore provide a customized, user-centric shopping experience.

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