E-grāmata: Deep Learning Approach for Natural Language Processing, Speech, and Computer Vision: Techniques and Use Cases

"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, andvisual 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-worldcase 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 provides an overview of general deep learning methodology and its applications of natural language processing (NLP), speech and computer vision tasks.

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.