Introduction
In the current era of increasing complexity and hierarchy of business problems, there needs to be an advanced computer machine that thinks like a human and performs in a better manner to reduce human overhead and make more accurate decisions.
In contrast to it, Artificial Intelligence is the technological advancement to build and train the machines that perform instead of humans and contribute automated operations. It incorporates multiple techniques for machine learning or training, and deep learning is one of them.
The use of such ML techniques helps to resolve the complex and hierarchical problems in an automated, and more efficient as well as effective manner. It is potent to assist human decision-making and make the decisions more accurate and remarkable.
Deep Learning
Deep learning is the branch of artificial intelligence that instructs the machines on how to learn and train them to filter inputs, learn how to predict, or classify information. It is a confined version of machine learning that gives rise to the high standard of the learning environment. Along with this, in integration with the instructed machines, it also helps to detect objects and solves the complex problems that need the discovery of hidden patterns in the data. Moreover, it plays an important role in promoting the computer system that can make decisions without human intervention, create knowledge out of big data, and gain particular understanding like the human mind.
Some of the areas where deep learning has been utilized: -
Customer Relationship Management:
Companies like Netflix and Amazon enhanced their learning capabilities to provide a personalized experience to the viewer to recommend shows that are liked by them. Likewise, VIVO is using deep learning to build the next generation of data services for a personalized experience for users.
Computer Vision in Entertainment:
Deep learning is also used in the filmmaking process with the camera to study human body language in virtual characters. It incorporates computer vision in which cameras are programmed to classify, detect, and track visual objects.
Visual Recognition:
Deep learning has been used in visual recognition as images can be categorized based on faces, location, variety of people, detected in photographs according to data, events, etc.
Fraud Detection:
Deep learning is also being used for fraud detection in the sectors like banking and monetary where there is a high chance of getting fraud with money transactions that are going digital. Fraud detection and prevention are being done based on identifying the contour in customer transactions, identifying behavior, and outliers.
Automated Photo Description:
Deep learning will automatically classify photographs. Likewise, Google photos automatically label all uploaded photos. One of the examples is Facebook that creates albums of tagged pictures, timeline images, and mobile uploads.
Conclusion
In conclusion, it has been identified that Deep Learning has extensive scope in the technological world to modernize decision making. Moreover, supervise the machines to work beyond the human imagination and enhance their experience.
