Deep Learning is a computer science that takes a more advanced approach than Machine Learning. Deep Learning is about processing the largest amounts of data, which must be processed with enormous computing power. Data such as that encountered in facial recognition in a group of people, language translation, medical diagnosis, image recognition, or voice recognition.
The basis of the deep learning technique, Deep Learning, is artificial intelligence and neural networks that are based on human thinking. While Machine Learning works with linear algorithms, Deep Learning algorithms are hierarchically structured with increasing complexity. In Deep Learning, the implementation of a word or an image is done through many training sessions, where a concept or an object is constantly deepened through image motifs until the implementation has the desired accuracy. The process requires an enormous amount of data, it can be based on thousands of images, and works with Big Data analytics. After that, the program can name the term based on a visual representation.
Application areas for Deep Learning are in autonomous driving, medical research and analysis, industrial automation, image recognition and speech recognition, translation activities, network security, and various other fields. For example, autonomous driving involves lane recognition, traffic light detection, traffic sign recognition, and pedestrian detection. In medical research, Deep Learning can be used to detect and identify cancer cells, and in electronics, it's about speech and voice recognition.