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Deep Learning Approach for Natural Language Processing, Speech, and Computer VisionНазвание: Deep Learning Approach for Natural Language Processing, Speech, and Computer Vision: Techniques and Use Cases
Автор: L. Ashok Kumar, D. Karthika Renuka
Издательство: CRC Press
Год: 2023
Страниц: 246
Язык: английский
Формат: pdf (true)
Размер: 30.9 MB

Deep Learning Approach for Natural Language Processing, Speech, and Computer Vision provides an overview of general deep learning methodology and its applications of Natural Language Processing (NLP), speech and Computer Vision tasks. It simplifies and presents the concepts of Deep Learning in a comprehensive manner, with suitable, full-fledged examples of Deep Learning models, with an aim to bridge the gap between the theory and the applications using case studies with code, experiments, and supporting analysis.

Voice-based assistants, AI-based chatbots, and advanced driver assistance systems are examples of applications that are becoming more common in daily life. In particular, the profound success of deep learning in a wide variety of domains has served as a benchmark for the many downstream applications in Artificial Intelligence (AI). Application areas of AI include natural language processing (NLP), speech, and computer vision. The cutting-edge deep learning models have predominantly changed the perspectives of varied fields in AI, including speech, vision, and NLP. In this book, we made an attempt to explore the more recent developments of deep learning in the field of NLP, speech, and computer vision. With the knowledge in this book, the reader can understand the intuition behind the working of natural language applications, speech, and computer vision applications. NLP is a part of AI that makes computers to interpret the meaning of human language. NLP utilizes machine learning and deep learning algorithms to derive the context behind the raw text. Computer vision applications such as advanced driver assistance systems, augmented reality, virtual reality, and biometrics have advanced significantly. With the advances in deep learning and neural networks, the field of computer vision has made great strides in the last decade and now outperforms humans in tasks such as object detection and labeling. This book gives an easy understanding of the fundamental concepts of underlying deep learning algorithms to the students, researchers, and industrial researchers as well as anyone interested in deep learning and NLP. It serves as a source of motivation for those who want to create NLP, speech, and computer vision applications.

Features:

- Covers latest developments in Deep Learning techniques as applied to audio analysis, Computer Vision, and Natural Language Processing
- Introduces contemporary applications of Deep Learning techniques as applied to audio, textual, and visual processing
- Discovers Deep Learning frameworks and libraries for NLP, speech and computer vision in Python
- Gives insights into using the tools and libraries in Python for real-world applications
- Provides easily accessible tutorials, and real-world case studies with codes to provide hands-on experience

This book is aimed at researchers and graduate students in computer engineering, image, speech, and text processing.

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