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Features and Applications of Cognitive Computing



Cognitive computing describes those technological platforms that are especially based on scientific disciplines of signal processing and artificial intelligence. These platforms include machine learning, reasoning, object recognition, speech recognition, and natural language processing. In the present day, cognitive computing is referred to as new software and hardware that can mimic the functioning of the human brain and can improve decision making. Cognitive computing connects data adaptive page displays and data analysis to adjust the contents for a specific kind of audience. In this article, I will discuss the features and applications of cognitive computing.

Features and Use Cases

Cognitive computing is a modern form of computing with the objective of creating accurate models about human brain senses, reasons and also respond to different stimulus. Cognitive computing has some features. Cognitive computing is adaptive; it learns the changes in the information and adapts itself to the change. It resolves any kind of ambiguity and also tolerates unpredictability. It is engineered to feed on different real time dynamic data. Cognitive computing is interactive; it interacts with the users easily as the users can explain their needs easily and comfortably. It also interacts with the different processors, cloud services and devices. It is stateful and iterative; it helps in defining various problems by finding any other source or by asking questions. It also remembers previous interactions and might use that information to define the current problem. Cognitive computing is contextual. It understands, identifies and extracts different contextual elements like meaning, syntax, time, location, appropriate domain, regulations, task, process, and goals. They can draw different information sources which include both unstructured and structured digital information. The cases in which cognitive computing is used are speech recognition, face detection, sentiment analysis, risk detection, fraud detection, and behavioral recommendations.



Application of Cognitive computing

Cognitive computing is used for educational purposes. It is a huge driving force in education for the students. The application of cognitive computing inside the classroom is in the form of personalized assistance for every individual student. Cognitive assistance helps in relieving the stress of the teacher and also helps in enhancing the learning experience of the students. There are some students who face problem in a particular subject or some students do not feel comfortable while interacting with the teacher; cognitive assistance eliminates these problems and helps the student to regain his or her confidence to perform properly in the classroom.  Assistance can help in various ways like creating different lesson plans for different subjects or provide aid to the students when it is needed. Cognitive computing is also used in healthcare or on medical grounds. Different technological companies are developing technology that includes cognitive computing to be used in medical fields. The main goal of cognitive devices is to identify and classify. This trait is very helpful for identifying and studying carcinogens. This technology helps in evaluating the information about any patient. It also helps in looking through the entire medical records of the patients in depth.

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Cognitive computing involves many concepts of data science. So without a proper data science course Cognitive computing is not possible. ExcelR in Pune is one of the most trusted sources of Data Science Training in Pune on which the student can trust.


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