Deep Learning : Explained

Deep Learning is also called as Deep Structured learning or HIERARCHICAL learning.
This is the process that undergoes completely or partially in the presence of a supervising expert and is assigned a specific task and accomplish the one without the supervision of anyone. There comes the topic of neural networks or artificial intelligence and machine learning and their complex algorithms.

This quickly attained a great demand in people and thereafter the main production, implementation and publicity started proving the abilities of deep learning in many fields that may be Computervision, Audio recognition, Social network filtering, machine translation, Bioinformatics and drug design.Where this produced results that are comparable with some superior expert human beings.
So coming to the architecture this is a neural network based architecture and is a class of machine learning algorithms that:
1.Uses cascaded multiple layers of nonlinear processing units for future extraction of information
2.This may be supervised or unsupervised(pattern analysis)

This acts similar to our brain in making decisions through neurons but here they are replaced by many complex networks connected by functions and moduled architecture (that might be a microcontroller or a small sensor system)

here all the thing that we see is the output and the input and in no way, we are going to see what is happening in the hidden layer of the network that is connected through many connections through many algorithms and functions.


1.Speech recognition
In this, we are just going to use the algorithms completely to know about the language that is being spoken by the speaker and Act or Answer accordingly and do the task.

This would surely bring Apple Siri and Android Google assistant, Your are right but they are not very complex and just use small algorithms to answer and meet our demands, but coming to actual thing involved in deep learning is completely identifying one in many and just separate and act according to order of the master or owner.


2. Image recognition

We were all familiar with this and have become fans of it after the release of Apple X face recognition technology this primarily uses the dimensions of the face and apply complex algorithms and recognize the one when asked to do, or in the situation that is supposed to do so.This would make things easier in tracking and identification of people through a simple camera.
The high-end use I found is in the  Self Driving Cars that could entirely change the mindset of people towards accidents and could prevent them since they are programmed in such a way that no harm should happen to any individual.

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3. Visual Art Processing

This is the one that makes a visual from some simple words of us and shows us visually. This found a lot of uses in many industries.


4.Natural language processing

A very interesting topic on this language manipulation and conversion from one to another(this is the very basic one but most famous one).This includes the most famous google translate and many apps including Grammarly that make language understanding, contextual entity linking, Write style recognition and many more.

5. Drug discovery and Toxicology

This also found a great usage in drug discovery and toxic identification in medication (even include targeted drug delivery system that was developed by the researchers at MIT).
The main role is to identify the type and information of the specific drug. And this is even done by using the basic information provided initially in programming.

6.Advertising

Nowadays this is being used by the advertisers to make auto advertising methods with deep learning that could make their task of acquiring people easily to their company using random programs through deep learning. This would help a lot.

7. BioInformatics

This is completely related to the human being activity and completely monitor the activity of the one and help him to do the required things that are supposed to do by him at that moment.
This includes all type of medical assistants that are connected to our body through sensors and monitored through a mobile phone or any device linked.


Conclusion:

The main problem with this is the CYBERTHREAT. This is the main problem with this as this could manipulate or make some small change in any single area could change the entire system.
For example in image recognition, if anyone makes a small change that may show one person for another or may think all are similar and give access to all this is called "Adversarial Attack".
Similarly "Data Poisoning" ruining something with malware that generally attacks after getting downloaded from the internet.



Let's wait for the fantastic developments in this field.and do our best in this field.

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