What is Deep learning: Excerpts and suggestions?

As of now, humans have already reaped maximum benefits from artificial intelligence or the AI technology. But, now the technology of deep learning has come up as an even more advanced version of the AI technology that is solely inspired from the process of how actually the human brain works. To say in a nutshell, the deep learning technology thrives better on a single formula. It is, the more data you put into it, the more effectively it will respond to the different forms of new data out there. Hence, it does not require the assistance of any type of human intervention while deciphering each of those new data sets. So, let’s have a glimpse at some of the basic stages that are included in the deep learning technology and that answers the question effectively that what is deep learning all about. 

The Various Stages of the Deep Learning Technology

Some of the stages that are indispensably included in the deep learning technology can be considered as follows:

1.      Preparation: This allows the data scientists to prepare a wide range of data samples and to learn about how to train a neural network effectively which is conventionally termed as the ‘brain’ network. Some of these data samples include different types of labelled files comprising both benign and malicious types of files.

2.      Training: This stage includes exposure of the ‘brain’ network to the various forms of raw data pertaining to the wide range of sample files out there. This helps the files to instinctively identify the various types of malicious code via the usage of the GPU technology. The usage of the GPU tool remarkably reduces the training phase from months to that of 24-48 hours at the most. 

3.      The Detection Stage: While the training phase remains ongoing, the network of ‘brain’ commences to detect the different types of malware threats out there. It does so by scanning the different types of raw data which each of these malware threats gets exposed to. 

4.      The Stage of Prediction: This stage brings the network of brain to the level of prediction. This allows the ‘brain’ network to identify any type of file that is inflicted by any sort of malware threat and is applicable to all kinds of files. 

5.      Agent Creation: In this particular stage, the ‘brain’ network gets transformed into a lightweight powerful agent, hence, providing it with all those capabilities to turn the different types of Terabytes instincts to that of the Megabytes perspectives. 

6.      Agent Insertion: It has already been inferred that the network of brain is already a domain which is solely agnostic by nature. Hence, it can be put into the different types of end-points, servers as well as that of a wide range of mobile devices in relation to any type of organization, be it small, medium or large. 

7.      Agent Protection: In this particular stage, the agent will start checking different types of malicious files, be it a script, macro or that of anything else. It does not inflict the user experience or system performance in anyway, since it takes even less than a millisecond to check each of the files. 

8.      The final Prevention: This stage allows the agent to potentially detect any type malware file that is impinging the system performance of your machine to a great extent, be it the different types of zero days, APTs or that of the acquainted files. In this process, the benign files will be retained whereas the malicious files will be excluded from the system. 

A boon in the world Cyber Security

Right from the outdated ruled-based models to the conventional machine learning versions to that of the latest AI integrated version, deep learning technology has gone through various stages of its evolution and is now considered as an immensely apt tool in the world of cybersecurity. Its latest version of ‘On Demand Webinar’ prevents your various company data from getting inflicted with those unexpected cyber attacks by the various cyber criminals out there. This model has already been used earlier in various areas of concern like text understanding, computer vision and now finally in the field of cybersecurity.

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