Deep Learning Approach For Natural Language Processing Speech And Computer Vision
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Deep Learning Approach For Natural Language Processing Speech And Computer Vision
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Author : L. Ashok Kumar
language : en
Publisher: CRC Press
Release Date : 2023-05-22
Deep Learning Approach For Natural Language Processing Speech And Computer Vision written by L. Ashok Kumar and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2023-05-22 with Business & Economics categories.
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 theoretical and the applications using case studies with code, experiments, and supporting analysis. 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 code to provide hands-on experience. This book is aimed at researchers and graduate students in computer engineering, image, speech, and text processing.
Deep Learning Approach For Natural Language Processing Speech And Computer Vision
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Author : L. Ashok Kumar
language : en
Publisher:
Release Date : 2023
Deep Learning Approach For Natural Language Processing Speech And Computer Vision written by L. Ashok Kumar and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2023 with Computer vision categories.
"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 aim to bridge the gap between the theoretical and the applications using case studies with code, experiments, and supporting analysis. 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 code to provide hands-on experience. This book is aimed at researchers and graduate students in computer engineering, image, speech, and text processing"--
Deep Learning Research Applications For Natural Language Processing
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Author : Ashok Kumar, L.
language : en
Publisher: IGI Global
Release Date : 2022-12-09
Deep Learning Research Applications For Natural Language Processing written by Ashok Kumar, L. and has been published by IGI Global this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022-12-09 with Computers categories.
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.
Deep Learning In Natural Language Processing
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Author : Li Deng
language : en
Publisher: Springer
Release Date : 2018-05-23
Deep Learning In Natural Language Processing written by Li Deng and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2018-05-23 with Computers categories.
In recent years, deep learning has fundamentally changed the landscapes of a number of areas in artificial intelligence, including speech, vision, natural language, robotics, and game playing. In particular, the striking success of deep learning in a wide variety of natural language processing (NLP) applications has served as a benchmark for the advances in one of the most important tasks in artificial intelligence. This book reviews the state of the art of deep learning research and its successful applications to major NLP tasks, including speech recognition and understanding, dialogue systems, lexical analysis, parsing, knowledge graphs, machine translation, question answering, sentiment analysis, social computing, and natural language generation from images. Outlining and analyzing various research frontiers of NLP in the deep learning era, it features self-contained, comprehensive chapters written by leading researchers in the field. A glossary of technical terms and commonly used acronyms in the intersection of deep learning and NLP is also provided. The book appeals to advanced undergraduate and graduate students, post-doctoral researchers, lecturers and industrial researchers, as well as anyone interested in deep learning and natural language processing.
Natural Language Processing With Tensorflow
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Author : Thushan Ganegedara
language : en
Publisher: Packt Publishing Ltd
Release Date : 2018-05-31
Natural Language Processing With Tensorflow written by Thushan Ganegedara and has been published by Packt Publishing Ltd this book supported file pdf, txt, epub, kindle and other format this book has been release on 2018-05-31 with Computers categories.
Write modern natural language processing applications using deep learning algorithms and TensorFlow Key Features Focuses on more efficient natural language processing using TensorFlow Covers NLP as a field in its own right to improve understanding for choosing TensorFlow tools and other deep learning approaches Provides choices for how to process and evaluate large unstructured text datasets Learn to apply the TensorFlow toolbox to specific tasks in the most interesting field in artificial intelligence Book Description Natural language processing (NLP) supplies the majority of data available to deep learning applications, while TensorFlow is the most important deep learning framework currently available. Natural Language Processing with TensorFlow brings TensorFlow and NLP together to give you invaluable tools to work with the immense volume of unstructured data in today’s data streams, and apply these tools to specific NLP tasks. Thushan Ganegedara starts by giving you a grounding in NLP and TensorFlow basics. You'll then learn how to use Word2vec, including advanced extensions, to create word embeddings that turn sequences of words into vectors accessible to deep learning algorithms. Chapters on classical deep learning algorithms, like convolutional neural networks (CNN) and recurrent neural networks (RNN), demonstrate important NLP tasks as sentence classification and language generation. You will learn how to apply high-performance RNN models, like long short-term memory (LSTM) cells, to NLP tasks. You will also explore neural machine translation and implement a neural machine translator. After reading this book, you will gain an understanding of NLP and you'll have the skills to apply TensorFlow in deep learning NLP applications, and how to perform specific NLP tasks. What you will learn Core concepts of NLP and various approaches to natural language processing How to solve NLP tasks by applying TensorFlow functions to create neural networks Strategies to process large amounts of data into word representations that can be used by deep learning applications Techniques for performing sentence classification and language generation using CNNs and RNNs About employing state-of-the art advanced RNNs, like long short-term memory, to solve complex text generation tasks How to write automatic translation programs and implement an actual neural machine translator from scratch The trends and innovations that are paving the future in NLP Who this book is for This book is for Python developers with a strong interest in deep learning, who want to learn how to leverage TensorFlow to simplify NLP tasks. Fundamental Python skills are assumed, as well as some knowledge of machine learning and undergraduate-level calculus and linear algebra. No previous natural language processing experience required, although some background in NLP or computational linguistics will be helpful.
Deep Learning In Visual Computing And Signal Processing
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Author : Krishna Kant Singh
language : en
Publisher: CRC Press
Release Date : 2022-10-20
Deep Learning In Visual Computing And Signal Processing written by Krishna Kant Singh and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022-10-20 with Technology & Engineering categories.
An enlightening amalgamation of deep learning concepts with visual computing and signal processing applications, this new volume covers the fundamentals and advanced topics in designing and deploying techniques using deep architectures and their application in visual computing and signal processing. The volume first lays out the fundamentals of deep learning as well as deep learning architectures and frameworks. It goes on to discuss deep learning in neural networks and deep learning for object recognition and detection models. It looks at the various specific applications of deep learning in visual and signal processing, such as in biorobotics, for automated brain tumor segmentation in MRI images, in neural networks for use in seizure classification, for digital forensic investigation based on deep learning, and more.
Advanced Applications Of Generative Ai And Natural Language Processing Models
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Author : Obaid, Ahmed J.
language : en
Publisher: IGI Global
Release Date : 2023-12-21
Advanced Applications Of Generative Ai And Natural Language Processing Models written by Obaid, Ahmed J. and has been published by IGI Global this book supported file pdf, txt, epub, kindle and other format this book has been release on 2023-12-21 with Computers categories.
The rapid advancements in Artificial Intelligence (AI), specifically in Natural Language Processing (NLP) and Generative AI, pose a challenge for academic scholars. Staying current with the latest techniques and applications in these fields is difficult due to their dynamic nature, while the lack of comprehensive resources hinders scholars' ability to effectively utilize these technologies. Advanced Applications of Generative AI and Natural Language Processing Models offers an effective solution to address these challenges. This comprehensive book delves into cutting-edge developments in NLP and Generative AI. It provides insights into the functioning of these technologies, their benefits, and associated challenges. Targeting students, researchers, and professionals in AI, NLP, and computer science, this book serves as a vital reference for deepening knowledge of advanced NLP techniques and staying updated on the latest advancements in generative AI. By providing real-world examples and practical applications, scholars can apply their learnings to solve complex problems across various domains. Embracing Advanced Applications of Generative AI and Natural Language Processing Modelsequips academic scholars with the necessary knowledge and insights to explore innovative applications and unleash the full potential of generative AI and NLP models for effective problem-solving.
A Beginner S Approach A Deep Dive Into Computer Vision And Deep Learning
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Author : Prof. Krupali Rupesh Dhawale
language : en
Publisher: Chyren Publication
Release Date : 2025-06-09
A Beginner S Approach A Deep Dive Into Computer Vision And Deep Learning written by Prof. Krupali Rupesh Dhawale and has been published by Chyren Publication this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-06-09 with Antiques & Collectibles categories.
Advances In Visual Computing
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Author : George Bebis
language : en
Publisher: Springer Nature
Release Date : 2025-01-21
Advances In Visual Computing written by George Bebis and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-01-21 with Computers categories.
This two-volume set LNCS 15046 and 15047 constitutes the refereed proceedings of the 17th International Symposium, ISVC 2024, held at Lake Tahoe, NV, USA, during October 21-23, 2024. The 54 (60) full papers and 12 poster papers were carefully reviewed and selected from 120 submissions. A total of 8 (13) papers were also accepted for oral presentation in special tracks from 15 submissions. The papers cover the following topical sections: Part I: Deep Learning; Computer Graphics; Video Analysis and Event Recognition; Motion and Tracking; Detection and Recognition; Visualization, and Medical Image Analysis. Part II: Segmentation; Recognition; Generalization in Visual Machine Learning; Vision and Robotics for Agriculture; Virtual Reality; Applications, and Poster.
Representation Learning For Natural Language Processing
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Author : Zhiyuan Liu
language : en
Publisher: Springer Nature
Release Date : 2020-07-03
Representation Learning For Natural Language Processing written by Zhiyuan Liu and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020-07-03 with Computers categories.
This open access book provides an overview of the recent advances in representation learning theory, algorithms and applications for natural language processing (NLP). It is divided into three parts. Part I presents the representation learning techniques for multiple language entries, including words, phrases, sentences and documents. Part II then introduces the representation techniques for those objects that are closely related to NLP, including entity-based world knowledge, sememe-based linguistic knowledge, networks, and cross-modal entries. Lastly, Part III provides open resource tools for representation learning techniques, and discusses the remaining challenges and future research directions. The theories and algorithms of representation learning presented can also benefit other related domains such as machine learning, social network analysis, semantic Web, information retrieval, data mining and computational biology. This book is intended for advanced undergraduate and graduate students, post-doctoral fellows, researchers, lecturers, and industrial engineers, as well as anyone interested in representation learning and natural language processing.