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Deep Learning with PyTorch (Paperback)
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Deep Learning with PyTorch (Paperback)
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Every other day we hear about new ways to put deep learning to good
use: improved medical imaging, accurate credit card fraud
detection, long range weather forecasting, and more. PyTorch puts
these superpowers in your hands, providing a comfortable Python
experience that gets you started quickly and then grows with you as
you, and your deep learning skills, become more sophisticated. Deep
Learning with PyTorch teaches you how to implement deep learning
algorithms with Python and PyTorch. This book takes you into a
fascinating case study: building an algorithm capable of detecting
malignant lung tumors using CT scans. As the authors guide you
through this real example, you'll discover just how effective and
fun PyTorch can be. Key features * Using the PyTorch tensor API *
Understanding automatic differentiation in PyTorch * Training deep
neural networks * Monitoring training and visualizing results *
Interoperability with NumPy Audience Written for developers with
some knowledge of Python as well as basic linear algebra skills.
Some understanding of deep learning will be helpful, however no
experience with PyTorch or other deep learning frameworks is
required. About the technology PyTorch is a machine learning
framework with a strong focus on deep neural networks. Because it
emphasizes GPU-based acceleration, PyTorch performs exceptionally
well on readily-available hardware and scales easily to larger
systems. Eli Stevens has worked in Silicon Valley for the past 15
years as a software engineer, and the past 7 years as Chief
Technical Officer of a startup making medical device software. Luca
Antiga is co-founder and CEO of an AI engineering company located
in Bergamo, Italy, and a regular contributor to PyTorch.
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