Deep Learning with Python, 2nd Edition

Deep Learning with Python: Learn Best Practices of Deep Learning Models with PyTorch, 2nd Edition

eBook Details:

  • Paperback: 323 pages
  • Publisher: WOW! eBook; 2nd edition (April 24, 2021)
  • Language: English
  • ISBN-10: 1484253639
  • ISBN-13: 978-1484253632

eBook Description:

Deep Learning with Python: Learn Best Practices of Deep Learning Models with PyTorch, 2nd Edition

Master the practical aspects of implementing deep learning solutions with PyTorch, using a hands-on approach to understanding both theory and practice. This updated Deep Learning with Python, 2nd 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.

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

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 Deep Learning with Python, 2nd Edition explains the best practices in taking these models to production with PyTorch.

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1 Response

  1. December 6, 2021

    […] Deep Learning: A Visual Approach: A richly-illustrated, full-color introduction to deep learning that offers visual and conceptual explanations instead of equations. You’ll learn how to use key deep learning algorithms without the need for complex math. […]

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