Deep learning technology: A subgroup of Artificial intelligence

Deep learning is progressive fragment of machine learning. Presently, Artificial intelligence is flourishing arena with numerous practical applications and active research projects. As a part of AI, deep learning utilizes multi layered deep neural network, algorithms stimulated by the human brain and abstraction that makes sense of voluminous data. Though giant companies like Google, Microsoft and facebook, Baidu, Amazon, Tesla, Twitter, Nvidia are actively developing deep learning team to improve customer experience as still this technology is highly intricate for professionals to grasp.

     

In Simple form, Deep learning generates digital neural networks that imitate the interaction of neurons in the human brain. In contemporary period, such algorithms are useful in detecting objects in images, analyse sound waves to convert verbal speech to text or process natural human language into a structured format for analysis. Deep learning algorithms perform data analysis and interpretation without the help of human programmer.

 

Techniques of deep learning focus on the building Artificial neural network (ANN) using several neural layers. There are numerous deep leaning networks such as multilayer perception (MLP), Auto encoders (AE), convolution Neural network (CNN), and Recurrent Neural network (RNN).

 

Deep learning is flourishing in technical sphere because it focuses on customization and real time decision making and explosion of features and data sets. There are wide application of Deep learning such as customer experience, language recognition, computer vision, sentiment bases news aggregation, and robotics. Deep learning technology is used to enhance airport security. Deep learning technology can detect real time fraud. Deep learning is a significant algorithm used in cyber security areas. In any firm, network intrusion detecting system detects the security compromises but it may also produce false results due to time consuming and low latency of audition files. By the use of deep learning approaches, it can be improved. Deep learning technology also helps in detecting threats to internet of things.

 

Key market applications of deep learning are:

 

-       Natural Language Processing Software: This tool aids the computer decipher messages or text.

-       Image Recognition Software: This tool facilitates the computer to search, sort, and segment for object detection.

-       Speech Recognition Software: This tool permits humans to interact with their smart gadgets.

 

With superb benefits, Deep learning technology has several challenges such as it works with huge amount of data. As deep learning techniques have become central part for numerous security applications such as malware detection software, self-driving cars, there are adverbial attacks of many deep learning applications also in real world.

 

To bind up technical threads, it is well observed that technology is thriving with special features. Deep learning is modern and progressive segment of Artificial intelligence and it is beneficial in multiple disciplines. Deep learning uses machine learning algorithms to perform array of operations without backing of human. These approaches help to automate the process of detecting and preventing cyber-attacks and threats to organizations.