Deep Learning:
Deep learning is a machine learning approach that directs computers to do what is normal to humans. This is an important aspect of data science, which involves predictive and statistical modelling. It is particularly helpful for data scientists who are responsible for gathering, processing, and interpreting vast volumes of data. Deep learning makes this process quicker and simpler.
Deep learning is a gateway to voice control on customer devices such as televisions, laptops, tablets, and hands-free speakers.
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Deep learning has achieved recognition accuracy at higher levels than even earlier. This helps client electronics to satisfy user expectations and is important for safety apps such as driver less cars.
Two important reasons for using Deep Learning are discussed below.
- Deep learning involves a large number of labelled data.
- Deep learning needs powerful computing power.
Application of Deep Learning
Medical Research:
Different researchers are focusing on deep learning, So they can create a device that automatically identifies a defect or disease in the body by simply following their patterns. Cancer researchers use deep learning apps to automatically identify cancer cells.
Defence and Aerospace:
In different security fields, deep learning is used to identify any unwanted areas of interest or can be used to find areas of interest using environmental aspects. Using this data, we can give the commands or orders to the troops if it is safe or unsafe to function in the area.
Automated Driving:
Nowadays, Automated driving is now becoming one of the most emerging problems. Several companies apply deep learning technology to the development of an automated vehicle that does not require human supervision to operate. Objects such as stop signs and traffic signals are automatically identified.
Industrial Automation:
Deep learning aims to improve the safety of workers around heavy machinery by automatically detecting when individuals or items are within an unprotected distance from machines.
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