Deep Learning Approach for Natural Language Processing, Speech, and Computer Vision 1st Edition

Deep Learning Approach for Natural Language Processing, Speech, and Computer Vision — 1st Edition by L. Ashok Kumar and D. Karthika Renuka is a contemporary, practical guide that brings together the three pillars of AI: NLP, speech processing, and computer vision. Clear explanations meet real-world relevance, making complex concepts accessible to students, researchers, and professionals across India, Europe, North America, and beyond.

This book opens with foundational principles of neural networks and optimization, then moves swiftly into applied architectures—convolutional and recurrent networks, LSTMs, attention and Transformer models—showing how these methods power language understanding, automatic speech recognition, and image analysis. Practical chapters illustrate preprocessing, feature extraction, model training, and evaluation, while case-driven examples demonstrate tasks such as sentiment analysis, speech-to-text, object detection, and image segmentation.

Readers gain actionable insight into building scalable systems: best practices for data preparation, transfer learning, fine-tuning pre-trained networks, and handling multilingual or noisy audio/video inputs. Emphasis on contemporary trends and evaluation metrics ensures that learners can confidently transition from theory to implementation in industry or academic projects.

Ideal for advanced undergraduates, postgraduates, data scientists, and software engineers seeking a unified resource on deep learning applications, this edition balances rigor with readability. If you’re aiming to develop production-ready models or strengthen your AI portfolio, this book is a compact, authoritative companion.

Order your copy today and start mastering deep learning techniques that drive modern NLP, speech recognition, and computer vision solutions worldwide.

Note: eBooks do not include supplementary materials such as CDs, access codes, etc.