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Deep Learning with C++. Design and deploy neural networks using CUDA for high-performance AI in C++ Bill Chen, Vikash Gupta

(ebook) (audiobook) (audiobook) Język publikacji: angielski
Deep Learning with C++. Design and deploy neural networks using CUDA for high-performance AI in C++ Bill Chen, Vikash Gupta - okladka książki

Deep Learning with C++. Design and deploy neural networks using CUDA for high-performance AI in C++ Bill Chen, Vikash Gupta - okladka książki

Deep Learning with C++. Design and deploy neural networks using CUDA for high-performance AI in C++ Bill Chen, Vikash Gupta - audiobook MP3

Deep Learning with C++. Design and deploy neural networks using CUDA for high-performance AI in C++ Bill Chen, Vikash Gupta - audiobook CD

Autorzy:
Bill Chen, Vikash Gupta
Wydawnictwo:
Packt Publishing (Z chęcią przeczytam książkę w języku polskim)
Ocena:
Bądź pierwszym, który oceni tę książkę
Stron:
610
Dostępne formaty:
     PDF
     ePub
Ebook
125,10 zł 139,00 zł (-10%)
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Do przechowalni

Deep learning systems often struggle to meet performance demands in real-time and production environments. This book shows you how to build high-performance deep learning systems in C++, enabling efficient and scalable artificial intelligence (AI) in resource-constrained environments where performance matters.
You’ll start by setting up a complete C++ deep learning environment and implementing core neural networks from scratch. As you progress, you’ll build advanced architectures, including Convolutional Neural Networks (CNNs), Recurrent Neural Networks (RNNs), Long Short-Term Memory Networks (LSTMs), Generative Adversarial Networks (GANs), and Transformers, using C++, CUDA, and PyTorch’s C++ API. The book then focuses on model quantization and compression. It will guide you through the model deployment process in production with robust monitoring and explainability. You’ll also explore distributed training and techniques for real-time inference in performance-critical domains.
By the end of this book, you’ll be able to design, optimize, and deploy deep learning systems in C++ that are production-ready, scalable, and efficient across multiple industries.

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O autorach książki

Xi Chen has graduated with Ph.D. in Biochemical and a Master in Statistics from the University of Kentucky. He is working as a certified NVidia Computer Vision (CV), CUDA and Deep Learning instructor. During his graduate career, he has led CV and deep learning related workshops. He also has published papers on topics of autonomic driving, reinforcement learning, and deep learning.
Vikash Gupta, Ph.D., CIIP, is a Senior Research Scientist at Amazon Web Services (AWS), based in Seattle, Washington. He earned his Ph.D. in Computational Biology from INRIA, France, where his research centered on neuroimaging and statistical modeling. At AWS, he applies deep learning and artificial intelligence to advance medical imaging technologies, contributing to open-source initiatives such as the MONAI framework for healthcare. A Certified Imaging Informatics Professional, he has authored over 15 peer-reviewed publications

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