SKU/Artículo: AMZ-B0FXR7MYP9
Building Multimodal AI with Python: A Developer’s Guide to Unified Learning
Format:
Kindle
Detalles del producto
Disponibilidad:
Fuera de stock
Fuera de stock
Peso con empaque:
0.15 kg
0.15 kg
Devolución:
Sí
Sí
Condición
Nuevo
Nuevo
Producto de:
Amazon
Amazon
Viaja desde
USA
USA
Sobre este producto
- Building Multimodal AI with Python: A Developer’s Guide to Unified Learning is a complete, hands-on guide to one of the most transformative frontiers in artificial intelligence—multimodal learning, where machines combine text, images, audio, and video to think and learn like humans.Traditional AI models focus on a single data type, but the future of intelligence lies in unifying multiple modalities to create systems that understand context holistically. This book takes you step by step through the theory, architecture, and implementation of multimodal AI systems using Python, helping you build models that can see, listen, read, and reason simultaneously.Starting from foundational concepts, you’ll explore how computer vision, natural language processing, and speech recognition work together within unified AI frameworks. Each chapter combines clear explanations, mathematical insight, and real-world coding projects, using leading Python libraries such as TensorFlow, PyTorch, and Hugging Face.You’ll develop complete projects including image captioning, audio-visual sentiment analysis, and cross-modal retrieval, gaining a deep understanding of how to synchronize different data sources into cohesive AI workflows. The book also covers optimization techniques, model fusion strategies, and deployment practices, ensuring your applications are not only intelligent but also scalable and production-ready.Inside you will learn:The fundamentals and principles of multimodal learning and unified intelligence.How to combine vision, language, and audio models using Python.Real-world implementations of image captioning, emotion recognition, and multimodal retrieval.Step-by-step integration using TensorFlow, PyTorch, and multimodal libraries.Techniques for optimizing, scaling, and deploying multimodal systems.How to design pipelines that bridge human-like perception and machine reasoning.Who this book is for:Students and Beginners entering AI through structured, easy-to-follow examples.Python Developers and ML Enthusiasts looking to expand into multimodal systems.Researchers and Data Scientists building scalable, real-world multimodal applications.Industry Professionals designing AI systems that interpret and integrate diverse data types.What sets this book apart is its perfect balance of theory, practice, and design thinking. You’ll not only learn how multimodal systems work—you’ll build them yourself, gaining the confidence to create next-generation AI applications that truly understand the world.By the end of this journey, you will have mastered the foundations, tools, and techniques to build intelligent systems capable of seeing, listening, reading, and reasoning as one.This is more than a book—it’s your roadmap to the future of AI integration and human-like machine intelligence.
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