Humans have the most advanced method of communication, which is
known as natural language. While humans can use computers to send
voice and text messages to each other, computers do not innately
know how to process natural language. In recent years, deep
learning has primarily transformed the perspectives of a variety of
fields in artificial intelligence (AI), including speech, vision,
and natural language processing (NLP). The extensive success of
deep learning in a wide variety of applications has served as a
benchmark for the many downstream tasks in AI. The field of
computer vision has taken great leaps in recent years and surpassed
humans in tasks related to detecting and labeling objects thanks to
advances in deep learning and neural networks. Deep Learning
Research Applications for Natural Language Processing explains the
concepts and state-of-the-art research in the fields of NLP,
speech, and computer vision. It provides insights into using the
tools and libraries in Python for real-world applications. Covering
topics such as deep learning algorithms, neural networks, and
advanced prediction, this premier reference source is an excellent
resource for computational linguists, software engineers, IT
managers, computer scientists, students and faculty of higher
education, libraries, researchers, and academicians.
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