THEORY AND APPLICATIONS IN DEEP LEARNING

Deep learning is a subfield of computer science that is currently focusing the majority of its attention on the areas of video, picture, text, and speech recognition, in addition to autonomous driving, robotics, healthcare, and other areas. This is in addition to other areas such as robotics and healthcare. Academics and academicians are currently showing a significant amount of interest in the field of deep learning. This is because it is a subfield of study that focuses a significant emphasis on achieving outcomes, which explains why this is the case. Rina Dechter was the first person to use the phrase "deep learning" in 1986, and the building of an intelligent computer that could emulate the functioning of the human brain was the driving force behind the expansion of this field of study. The term "deep learning" was coined by Rina Dechter, who was also the first person to use the term. The human brain, which is in charge of decision-making, is the most important organ in the body. In order for the brain to arrive at its conclusions, it takes in data through its five senses: sight, smell, touch, and hearing. Memory is another item that is stored in the brain, and it is this memory that may be used to solve complicated problems by drawing on experiences that have been gained in the past. Throughout the course of the past few decades, scientists have kept alive the dream that they may one day be able to design a computer with intellect comparable to that of our own brains. In order to make progress towards achieving this goal, they have initiated research into the fundamental make-up and operation of the human brain. One of the primary motivations behind the development of autonomous vehicles as well as robots that are capable of performing a variety of functions is the reduction in the number of collisions that take place along roadways. This can be accomplished through the use of robots that are multi-functional. Because it is estimated by the World Health Organization (WHO) that 1.35 million people lose their lives on the roads of the world each year, and since it is estimated that more than 90 percent of those deaths are the result of human errors that could have been avoided.