Generative Deep Learning 在线电子书 pdf 下载 txt下载 epub 下载 mobi 下载 2024


Generative Deep Learning

简体网页||繁体网页
David Foster 作者
O'Reilly Media
译者
2019-7-16 出版日期
330 页数
USD 68.18 价格
Paperback
丛书系列
9781492041948 图书编码

Generative Deep Learning 在线电子书 图书标签: 深度学习  机器学习  计算机科学  计算机  Machine_Learning  Deep_Learning  GANs  GAN   


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发表于2024-12-23


Generative Deep Learning 在线电子书 epub 下载 mobi 下载 pdf 下载 txt 下载 2024

Generative Deep Learning 在线电子书 epub 下载 mobi 下载 pdf 下载 txt 下载 2024

Generative Deep Learning 在线电子书 pdf 下载 txt下载 epub 下载 mobi 下载 2024



Generative Deep Learning 在线电子书 用户评价

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What I cannot create, I do not understand. - Richard Feynman

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作者拿naive bayes模型引出deep learning......No the guy doesn't know what he is talking about.....入门者看看代码的技术细节(包括一些GAN自带的问题)就行了。

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作者拿naive bayes模型引出deep learning......No the guy doesn't know what he is talking about.....入门者看看代码的技术细节(包括一些GAN自带的问题)就行了。

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Who needs kids when the AI gets it better.

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作者拿naive bayes模型引出deep learning......No the guy doesn't know what he is talking about.....入门者看看代码的技术细节(包括一些GAN自带的问题)就行了。

Generative Deep Learning 在线电子书 著者简介

David Foster is the co-founder of Applied Data Science, a data science consultancy delivering bespoke solutions for clients. He holds an MA in Mathematics from Trinity College, Cambridge, UK and an MSc in Operational Research from the University of Warwick.

David has won several international machine learning competitions, including the Innocentive Predicting Product Purchase challenge and was awarded first prize for a visualisation that enables a pharmaceutical company in the US to optimize site selection for clinical trials.

He is an active participant in the online data science community and has authored several successful blog posts on deep reinforcement learning including ‘How To Build Your Own AlphaZero AI’.


Generative Deep Learning 在线电子书 图书目录


Generative Deep Learning 在线电子书 pdf 下载 txt下载 epub 下载 mobi 在线电子书下载

Generative Deep Learning 在线电子书 图书描述

Generative modeling is one of the hottest topics in artificial intelligence. Recent advances in the field have shown how it’s possible to teach a machine to excel at human endeavors—such as drawing, composing music, and completing tasks—by generating an understanding of how its actions affect its environment.

With this practical book, machine learning engineers and data scientists will learn how to recreate some of the most famous examples of generative deep learning models, such as variational autoencoders and generative adversarial networks (GANs). You’ll also learn how to apply the techniques to your own datasets.

David Foster, cofounder of Applied Data Science, demonstrates the inner workings of each technique, starting with the basics of deep learning before advancing to the most cutting-edge algorithms in the field. Through tips and tricks, you’ll learn how to make your models learn more efficiently and become more creative.

Get a fundamental overview of deep learning

Learn about libraries such as Keras and TensorFlow

Discover how variational autoencoders work

Get practical examples of generative adversarial networks (GANs)

Understand how autoregressive generative models function

Apply generative models within a reinforcement learning setting to accomplish tasks

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