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foundation of deep learning, which has made substantial advancements in numerous areas
such as facial recognition, audio and image processing, speech recognition, natural
language processing, text categorization, and other tasks. Deep learning allows for the
correction of complex tasks and significant improvements in these areas [5]. Furthermore,
deep learning is equipped with various automatic classification systems. In Natural
Language Processing, for example, deep learning algorithms can analyze, categorize, and
pronounce words and phrases. Consequently, models created by expert deep learning
practitioners are extremely helpful in text analysis and upcoming technologies [2].
Additionally, deep learning systems collect data beyond standard word usage, including
information on the composition and characteristics of analyzed objects, such as the
construction, color, and size of objects in images. The high accuracy of deep learning
facilitates substantial gains through the creation of models and analytical techniques. This
allows for the study of speech, image, and video data in various fields. The vast processing
layers and breakthrough capabilities of deep learning will play a significant role in
enhancing user experience and creating innovative solutions in all future industries [3].
