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Dive into Deep Learning
Aston Zhang, Zachary C. Lipton, Mu Li, Alexander J. Smola
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R883
R836
Discovery Miles 8 360
Save R47 (5%)
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Ships in 12 - 17 working days
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Deep learning has revolutionized pattern recognition, introducing
tools that power a wide range of technologies in such diverse
fields as computer vision, natural language processing, and
automatic speech recognition. Applying deep learning requires you
to simultaneously understand how to cast a problem, the basic
mathematics of modeling, the algorithms for fitting your models to
data, and the engineering techniques to implement it all. This book
is a comprehensive resource that makes deep learning approachable,
while still providing sufficient technical depth to enable
engineers, scientists, and students to use deep learning in their
own work. No previous background in machine learning or deep
learning is required—every concept is explained from scratch and
the appendix provides a refresher on the mathematics needed.
Runnable code is featured throughout, allowing you to develop your
own intuition by putting key ideas into practice.
This book presents papers presented at the 4th EAI International
Conference on Robotic Sensor Networks. The conference explored the
integration of networks and robotic technologies, which has become
a topic of increasing interest for both researchers and developers
from academic fields and industries worldwide. The authors explore
how big networks are becoming the main tool for the next generation
of robotic research, owing to the explosive number of networks
models and the increased computational power of computers. The
papers discuss how these trends significantly extend the number of
potential applications for robotic technologies while also bringing
new challenges to the networks' communities. The 2nd EAI
International Conference on Robotic Sensor Networks was held online
on November 21-22, 2020.
Urbanization has dominated China's development landscape in recent
decades, yet the human costs of this economic achievement are
largely ignored in commentaries on the subject.Urbanization and
Public Health in China seeks to redress this imbalance by bringing
together academics and researchers from across China and Australia
to offer fresh perspectives on public health issues resulting from
urbanization. The analyses focus on issues of unequal access to
health services by the most vulnerable groups: the elderly and
rural-to-urban migrants. The book explores these issues through
demographic, epidemiological and environmental change in China over
the past three decades and identifies solutions to create a
healthier living environment in urban China.Other countries
undergoing similar rapid urbanization can learn vital lessons from
these challenges and solutions. This book provides a comprehensive
overview for academics and researchers working on urbanization in
developing nations, as well as a reference point for policy makers
and public health practitioners.
This book presents papers presented at the 4th EAI International
Conference on Robotic Sensor Networks. The conference explored the
integration of networks and robotic technologies, which has become
a topic of increasing interest for both researchers and developers
from academic fields and industries worldwide. The authors explore
how big networks are becoming the main tool for the next generation
of robotic research, owing to the explosive number of networks
models and the increased computational power of computers. The
papers discuss how these trends significantly extend the number of
potential applications for robotic technologies while also bringing
new challenges to the networks' communities. The 2nd EAI
International Conference on Robotic Sensor Networks was held online
on November 21-22, 2020.
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