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The artificial network that is used to perform complicated and sophisticated computations on large amounts of data is called data learning. The structure and function of the human brain create the base of this type of machine learning. Health care, entertainment and advertising are the industries that commonly use deep learning. 

Usually, self-learning representations are featured in deep learning algorithms but they also depend on the ANNs which replicate the way the brain computes information. 

Unknown elements are used in the input distribution so that features can be copied, objects can be grouped and important data patterns can be discovered during the process of training. 

 

How does it work?

Large sets of labelled data and neural network architectures are used to train the models of deep learning. They do not require manual feature extraction. It usually has a number of hidden layers and hence, it is referred to be deep. 

Neural network architectures are used in deep learning and so it is also called the deep neural networks. Going through each neural network layer makes the deep learning algorithm learn and work progressively in each layer. 

 

Uses of deep learning 

Deep learning delivers superhuman accuracy for image classification, detection of objects, image restoration and segmentation of images. 


1. Virtual assistants

They are assistants on our smart devices that use cloud-based applications and are able to comprehend the commands given in natural voice and complete tasks for the user. Their full capabilities can be explored only when there connected over the internet. The past experiences help them to evolve and deliver a better result every next time. 

2. Chatbots 

A chatbot is a feature that is used for interacting with the customer and social network site marketing and to send instant messages to the client. It uses the AI application so that it can chat online with the customers and help to solve problems by delivering automated responses to the inputs user give in. the different types of reactions are generated by the use of machine learning and algorithms of deep learning. 

3. Health care sector 

The health care sector has effectively used Deep learning. Quicker disease detection and diagnosis that are computer-aided are possible by using deep learning. It has made fighting with dangerous diseases like cancer and diabetic retinopathy possible through the process of medical imaging. Medical research and drug discovery also become better with deep learning. 

4. Entertainment 

Deep learning is a great process that helps companies like Amazon, Netflix, Spotify, youtube to enhance their customer experience by suggesting relevant songs, movies and video recommendations to their customers. This is possible because the user’s browsing history, interests and online usage undergoes deep learning and helps to customise their products and services. Audios to silent movies and subtitle generation are also possible through the Deep Learning technique. 

5. Robotics 

Making the robots perform tasks just the way humans do is a major use of deep learning. The robots that are built on deep learning stay updated in real-time to sense the obstacles which are further used to plan their journey in advance instantly. 

6. Advertising

Optimising the experience of a user is also a beneficiary of deep learning. It is used to positively increase the significance of ads and boost the campaigns. The cost per acquisition can also be dropped by using deep learning as it will enable ad networks. It makes target display advertising, bidding ads in real-time and creating predictive advertisements that are driven by the data. 

7. News segregation and detection of fake news 

Customising the news according to the user’s personality is also made possible by deep learning. Aggregation and filtering out the information of the news into various categories like social, political, economic etc according to the preference of the individual reader is also a capability of deep learning. Fake and biased news can be detected and removed from the timeline by the classifies developed by the neural networks and keep you warned if your privacy is breached. 

 

Deep learning helps to solve complicated problems even if the data is quite diverse, structureless and not independent. The importance of deep learning is being acknowledged in every field as it has brought about a revolution in everyone’s life by making tasks easier. 

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