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.
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.
in 6 offers
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.
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.
Last updated at 28/09/2024 07:14:01
Go to store
Affiliate Disclosure: We may receive a small commission for purchases made through this link at no extra cost to you. This helps support our site. Thank you!
Go to store
Go to store
Go to store
available 1 day ago
Low stock
available 4 days ago
Low stock
Affiliate Disclosure: We may receive a small commission for purchases made through this link at no extra cost to you. This helps support our site. Thank you!
available 5 days ago
Low stock
Affiliate Disclosure: We may receive a small commission for purchases made through this link at no extra cost to you. This helps support our site. Thank you!
See 9 more history offers
available 27 days ago
Low stock
Affiliate Disclosure: We may receive a small commission for purchases made through this link at no extra cost to you. This helps support our site. Thank you!
available 3 months ago
Low stock
available 3 months ago
Low stock
Affiliate Disclosure: We may receive a small commission for purchases made through this link at no extra cost to you. This helps support our site. Thank you!
available 6 months ago
Low stock
Affiliate Disclosure: We may receive a small commission for purchases made through this link at no extra cost to you. This helps support our site. Thank you!
available 7 months ago
Low stock
Affiliate Disclosure: We may receive a small commission for purchases made through this link at no extra cost to you. This helps support our site. Thank you!
available 7 months ago
Low stock
available 7 months ago
Low stock
Learning Deep Learning
$73.49 - $94.95
Compare 3 offers
Ai Machine Learning and Deep Learning
$168.00 - $210.00
Compare 4 offers
originally posted on manning.com
originally posted on manning.com
originally posted on manning.com
Imprint | Manning Publications |
Pub date | 16 Jun 2020 |
DEWEY edition | 23 |
Language | English |
Spine width | 32mm |
Updated about 4 hours ago
See 9 more history offers
Imprint | Manning Publications |
Pub date | 16 Jun 2020 |
DEWEY edition | 23 |
Language | English |
Spine width | 32mm |