Deep Learning com PyTorch, Segunda Edição
About this book
PyTorch core developer Howard Huang updates the bestselling original Deep Learning with PyTorch with new insights into the transformers architecture and generative AI models.Instantly familiar to anyone who knows PyData tools like NumPy, PyTorch simplifies deep learning without sacrificing advanced features. In this book you’ll learn how to create your own neural network and deep learning systems and take full advantage of PyTorch’s built-in tools for automatic differentiation, hardware acceleration, distributed training, and more. You’ll discover how easy PyTorch makes it to build your entire DL pipeline, including using the PyTorch Tensor API, loading data in Python, monitoring training, and visualizing results. Each new technique you learn is put into action with practical code examples in each chapter, culminating into you building your own convolution neural networks, transformers, and even a real-world medical image classifier.In Deep Learning with PyTorch, Second Edition you’ll find:• Deep learning fundamentals reinforced with hands-on projects• Mastering PyTorch's flexible APIs for neural network development• Implementing CNNs, transformers, and diffusion models• Optimizing models for training and deployment• Generative AI models to create images and textAbout the technologyThe powerful PyTorch library makes deep learning simple—without sacrificing the features you need to create efficient neural networks, LLMs, and other ML models. Pythonic by design, it’s instantly familiar to users of NumPy, Scikit-learn, and other ML frameworks. This thoroughly-revised second edition covers the latest PyTorch innovations, including how to create and refine generative AI models.About the bookDeep Learning with PyTorch, Second Edition shows you how to build neural network models using the latest version of PyTorch. Clear explanations and practical projects help you master the fundamentals and explore advanced architectures including transformers and LLMs. Along the way you
Perfil do leitor
· 600 páginas · ≈ 11 h 07 m · Moderado
Quanto tempo leva para ler Deep Learning with PyTorch, Second Edition?
Cerca de ≈ 11 h 07 m — 600 páginas, considerando aproximadamente 250 palavras por página a 225 palavras por minuto.
Quantas páginas tem Deep Learning with PyTorch, Second Edition?
600 páginas em sua edição mais lida.
Qual é o gênero de Deep Learning with PyTorch, Second Edition?
Ele está nas estantes de Science.
Deep Learning with PyTorch, Second Edition está em domínio público?
Não — ainda está sob direitos autorais.
Quem escreveu Deep Learning with PyTorch, Second Edition?
Luca Antiga, Eli Stevens, howard huang & Thomas Viehmann.