Pro Deep Learning with TensorFlow: A Mathematical Approach to Advanced Artificial Intelligence 免积分下载...

本书提供深度学习的全面指南,涵盖数学基础到实际应用。通过TensorFlow,读者将学会构建和部署深度学习解决方案,包括卷积神经网络、自然语言处理、无监督学习等。随书附带的代码示例可在IPython记事本和脚本中运行。
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Pro Deep Learning with TensorFlow

使用tensorflow轻松地在生产中部署深度学习解决方案。您还将开发所需的数学理解和直觉,以便自己发明新的深度学习体系结构和解决方案。

提供实用、动手的专业知识,这样您就可以从头开始学习深度学习,并部署有意义的深层学习解决方案。 本书将允许您快速使用TensorFlow快速加速,并优化不同的深度学习架构。

深入学习的所有实际方面都在本书中得到了强调。您将能够使用演示的原型来构建新的深度学习应用程序。本书中的代码以IPython记事本和脚本的形式提供,它允许您尝试示例并以有趣的方式扩展它们。

你将拥有数学基础和科学知识,从事这一领域的研究并回馈社会。

目录

Chapter 1: Mathematical Foundations
Chapter 2: Introduction to Deep-Learning Concepts and TensorFlow
Chapter 3: Convolutional Neural Networks
Chapter 4: Natural Language Processing Using Recurrent Neural Networks
Chapter 5: Unsupervised Learning with Restricted Boltzmann Machines and Auto-encoders

Chapter 6: Advanced Neural Networks

免积分下载地址:Apress Pro Deep Learning with TensorFlow.pdf

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转载于:https://my.oschina.net/u/3070312/blog/2997676

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Pro Deep Learning with TensorFlow is a practical and mathematical guide to deep learning using TensorFlow. Deep learning is a branch of machine learning where you model the world in terms of a hierarchy of concepts. This pattern of learning is similar to the way a human brain learns, and it allows computers to model complex concepts that often go unnoticed in other traditional methods of modeling. Hence, in the modern computing paradigm, deep learning plays a vital role in modeling complex real-world problems, especially by leveraging the massive amount of unstructured data available today. Because of the complexities involved in a deep-learning model, many times it is treated as a black box by people using it. However, to derive the maximum benefit from this branch of machine learning, one needs to uncover the hidden mystery by looking at the science and mathematics associated with it. In this book, great care has been taken to explain the concepts and techniques associated with deep learning from a mathematical as well as a scientific viewpoint. Also, the first chapter is totally dedicated toward building the mathematical base required to comprehend deep-learning concepts with ease. TensorFlow has been chosen as the deep-learning package because of its flexibility for research purposes and its ease of use. Another reason for choosing TensorFlow is its capability to load models with ease in a live production environment using its serving capabilities. In summary, Pro Deep Learning with TensorFlow provides practical, hands-on expertise so you can learn deep learning from scratch and deploy meaningful deep-learning solutions. This book will allow you to get up to speed quickly using TensorFlow and to optimize different deep-learning architectures. All the practical aspects of deep learning that are relevant in any industry are emphasized in this book. You will be able to use the prototypes demonstrated to build new deep-learning applications. The code presented in th
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