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Artículo: AMZ-B0FKM7R28L
Neural Networks and Deep Learning with PyTorch: Master Engineering with PyTorch, Python, NumPy, TorchVision, HuggingFace, CUDA, PyTorch Lightning, and TensorBoard
Format:
Paperback
Detalles del producto
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En stock
En stock
Peso con empaque
0.64 kg
0.64 kg
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Sí
Sí
Condición
Nuevo
Nuevo
Producto de
Amazon
Amazon
Viaja desde
USA
USA
Sobre este producto
- What if you could build powerful neural networks with ease and deploy them to solve real-world problems? This book equips you with the tools and knowledge to create, optimize, and deploy deep learning models using PyTorch, one of the most flexible and widely used frameworks today. Whether you're a beginner or an experienced practitioner, this guide offers practical, hands-on insights to elevate your skills. The book focuses on building and deploying deep learning systems, guiding you through every step of the process. It starts with PyTorch basics, progresses to advanced architectures like transformers and GANs, and culminates in production-ready deployment with Docker and FastAPI. Each chapter combines clear explanations, expert commentary, and extensive code examples, ensuring you can apply concepts immediately. Drawing from real-world experience, the author shares lessons learned from debugging gradients to scaling APIs, making complex topics approachable and engaging. What sets this book apart? It covers critical topics with depth and clarity, including:Transformers and NLP with HuggingFace – Master the self-attention mechanism and fine-tune BERT for text classification, leveraging HuggingFace’s powerful tools.Generative Models – Explore autoencoders, VAEs, and GANs to generate new data, with practical MNIST examples.Accelerating Training with CUDA and GPUs – Harness GPU power to speed up training, with multi-GPU strategies.Model Export and Serving – Export models to ONNX and serve them via FastAPI for production use.Conclusion and Future Directions – Recap key concepts and explore trends like MLOps and AI ethics.Readers gain actionable skills in model development, optimization, visualization, and deployment, alongside insights into emerging trends like large-scale models and ethical AI. The book’s conversational tone and real-world examples make learning intuitive and inspiring. Ready to build cutting-edge deep learning systems? Get your copy today and start creating, optimizing, and deploying models with confidence!
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