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Books > Computing & IT > Applications of computing > Artificial intelligence > Machine learning
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Deep Learning with Python - Learn Best Practices of Deep Learning Models with PyTorch (Paperback, 2nd ed.)
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Deep Learning with Python - Learn Best Practices of Deep Learning Models with PyTorch (Paperback, 2nd ed.)
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Master the practical aspects of implementing deep learning
solutions with PyTorch, using a hands-on approach to understanding
both theory and practice. This updated edition will prepare you for
applying deep learning to real world problems with a sound
theoretical foundation and practical know-how with PyTorch, a
platform developed by Facebook's Artificial Intelligence Research
Group. You'll start with a perspective on how and why deep learning
with PyTorch has emerged as an path-breaking framework with a set
of tools and techniques to solve real-world problems. Next, the
book will ground you with the mathematical fundamentals of linear
algebra, vector calculus, probability and optimization. Having
established this foundation, you'll move on to key components and
functionality of PyTorch including layers, loss functions and
optimization algorithms. You'll also gain an understanding of
Graphical Processing Unit (GPU) based computation, which is
essential for training deep learning models. All the key
architectures in deep learning are covered, including feedforward
networks, convolution neural networks, recurrent neural networks,
long short-term memory networks, autoencoders and generative
adversarial networks. Backed by a number of tricks of the trade for
training and optimizing deep learning models, this edition of Deep
Learning with Python explains the best practices in taking these
models to production with PyTorch. What You'll Learn Review machine
learning fundamentals such as overfitting, underfitting, and
regularization. Understand deep learning fundamentals such as
feed-forward networks, convolution neural networks, recurrent
neural networks, automatic differentiation, and stochastic gradient
descent. Apply in-depth linear algebra with PyTorch Explore PyTorch
fundamentals and its building blocks Work with tuning and
optimizing models Who This Book Is For Beginners with a working
knowledge of Python who want to understand Deep Learning in a
practical, hands-on manner.
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