Deep Learning

Deep Learning pdf epub mobi txt 電子書 下載2025

Ian Goodfellow is Research Scientist at OpenAI. Yoshua Bengio is Professor of Computer Science at the Université de Montréal. Aaron Courville is Assistant Professor of Computer Science at the Université de Montréal.

出版者:The MIT Press
作者:Ian Goodfellow
出品人:
頁數:800
译者:
出版時間:2016-11-11
價格:USD 72.00
裝幀:Hardcover
isbn號碼:9780262035613
叢書系列:Adaptive Computation and Machine Learning
圖書標籤:
  • 深度學習 
  • 機器學習 
  • DeepLearning 
  • 人工智能 
  • AI 
  • MachineLearning 
  • 計算機 
  • 計算機科學 
  •  
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"Written by three experts in the field, Deep Learning is the only comprehensive book on the subject." -- Elon Musk, co-chair of OpenAI; co-founder and CEO of Tesla and SpaceX

Deep learning is a form of machine learning that enables computers to learn from experience and understand the world in terms of a hierarchy of concepts. Because the computer gathers knowledge from experience, there is no need for a human computer operator to formally specify all the knowledge that the computer needs. The hierarchy of concepts allows the computer to learn complicated concepts by building them out of simpler ones; a graph of these hierarchies would be many layers deep. This book introduces a broad range of topics in deep learning.

The text offers mathematical and conceptual background, covering relevant concepts in linear algebra, probability theory and information theory, numerical computation, and machine learning. It describes deep learning techniques used by practitioners in industry, including deep feedforward networks, regularization, optimization algorithms, convolutional networks, sequence modeling, and practical methodology; and it surveys such applications as natural language processing, speech recognition, computer vision, online recommendation systems, bioinformatics, and videogames. Finally, the book offers research perspectives, covering such theoretical topics as linear factor models, autoencoders, representation learning, structured probabilistic models, Monte Carlo methods, the partition function, approximate inference, and deep generative models.

Deep Learning can be used by undergraduate or graduate students planning careers in either industry or research, and by software engineers who want to begin using deep learning in their products or platforms. A website offers supplementary material for both readers and instructors.

具體描述

讀後感

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不知道中文翻譯版和github上的中文翻譯版一樣不,個人覺得github上的中文翻譯,翻譯的不錯。不過剛把前麵數學部分看完。但對比瞭一下人民郵電的中文版,怎麼纔500頁,而github上有700多頁,難道是排版導緻的嗎。深度學習入門經典書籍,填補瞭這一塊空白。前幾章的數學基礎,就...  

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這本書全麵瞭介紹瞭深度學習的主要方麵,包括基礎的數學基知識和機器學習知識,深度學習的實踐部分,以及深度學習的理論研究部分。全書組織結構清晰,由淺入深地循序漸進的介紹瞭深度學習的各個部分。實踐部分包括瞭經典的CNN, RNN等神經網絡,理論研究部分包括瞭經典的RBM,DB...  

評分

這本書寫的是比較有深度的,堪稱深度學習的聖經。隻是中文版翻譯的比較一般,part1和part2尚且可以一讀,至於part3,不知道譯者自己有沒有理解原文內容,像是逐詞直譯,非常拗口。part3有時間的話拿英文版的齣來看一看。 其中第一部分的數學和機器學習可以用來復習忘記的基礎知...  

用戶評價

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非常好的教材,可以結閤GitHub上的中文譯版看。

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非常好的一本書,每個從業者都該看看

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六星推薦。應該會二刷。期望有點大……讀到後麵感覺有點亂。四星吧……20170415

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他們起草的時候指齣他們一些公式錯誤,所以上麵有我的名字,哈哈

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非常好的一本書,每個從業者都該看看

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