Deep Learning (Adaptive Computation and Machine Learning series) Ian Goodfellow

US $76.49
大約HK$ 595.90
或講價
原價:US $89.99 (15% 折扣)這價格是什麼意思?
賣家提供的近期成交價
狀況:
很新
This item is new and unused however due to lack of proper packaging there is a a small scuff on the ... 閱讀更多內容關於物品狀況
距離減價活動結束時間: 5 日
手快有,手慢無! 1 人正在追蹤這件物品。
無後顧之憂! 免費運送及退貨。
見面交收或取貨:
可於Conway, Arkansas, 美國免費本地見面交收.
運送:
免費 USPS Ground Advantage®.
所在地:Conway, Arkansas, 美國
送達日期:
估計於 11月22日 (星期六)11月26日 (星期三)之間送達 運送地點 94104
估計運送時間是透過我們的獨家工具,根據買家與物品所在地的距離、所選的運送服務、賣家的運送紀錄及其他因素,計算大概的時間。送達時間會因時而異,尤其是節日。
如需即日發貨,請在以下時間內下單: 6  小時 38  分鐘
退貨:
30 日退貨. 由賣家支付退貨運費.
保障:
請參閱物品說明或聯絡賣家以取得詳細資料。閱覽全部詳情查看保障詳情
(不符合「eBay 買家保障方案」資格)

安心購物

高度評價賣家
值得信賴的賣家,發貨快,輕鬆退貨。 進一步了解- 超高度評價 — 會在新視窗或分頁中開啟
賣家必須承擔此刊登物品的所有責任。
eBay 物品編號:205317862213

物品細節

物品狀況
很新
狀況完好的書籍。封面發亮且沒有損壞,精裝本書籍含書皮。不存在缺頁或內頁受損,無褶皺或破損,同時也沒有對文字標注/標記,或在留白處書寫內容。內封面上標記極少。書籍的磨損和破損程度也很低。 查看所有物品狀況定義會在新視窗或分頁中開啟
賣家備註
“This item is new and unused however due to lack of proper packaging there is a a small scuff on the ...
Unit Type
Unit
Unit Quantity
1
ISBN
9780262035613
類別

關於產品

Product Identifiers

Publisher
MIT Press
ISBN-10
0262035618
ISBN-13
9780262035613
eBay Product ID (ePID)
228981524

Product Key Features

Number of Pages
800 Pages
Language
English
Publication Name
Deep Learning
Publication Year
2016
Subject
Intelligence (Ai) & Semantics, Computer Science
Type
Textbook
Subject Area
Computers
Author
Yoshua Bengio, Ian Goodfellow, Aaron Courville
Series
Adaptive Computation and Machine Learning Ser.
Format
Hardcover

Dimensions

Item Height
1.3 in
Item Weight
45.5 Oz
Item Length
9.3 in
Item Width
7.3 in

Additional Product Features

Intended Audience
Trade
LCCN
2016-022992
Reviews
[T]he AI bible... the text should be mandatory reading by all data scientists and machine learning practitioners to get a proper foothold in this rapidly growing area of next-gen technology., [T]he AI bible... the text should be mandatory reading by all data scientists and machine learning practitioners to get a proper foothold in this rapidly growing area of next-gen technology.-- Daniel D. Gutierrez , insideBIGDATA --
Dewey Edition
23
Illustrated
Yes
Dewey Decimal
006.3/1
Synopsis
An introduction to a broad range of topics in deep learning, covering mathematical and conceptual background, deep learning techniques used in industry, and research perspectives. "Written by three experts in the field, Deep Learning is the only comprehensive book on the subject." -Elon Musk , cochair of OpenAI; cofounder 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., An introduction to a broad range of topics in deep learning, covering mathematical and conceptual background, deep learning techniques used in industry, and research perspectives. "Written by three experts in the field, Deep Learning is the only comprehensive book on the subject." --Elon Musk , cochair of OpenAI; cofounder 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.
LC Classification Number
Q325.5.G66 2017

賣家提供的物品說明

賣家簡介

The Family Flips

99.4% 正面信用評價已賣出 3.21 萬 件物品

加入日期:8月 2014
We are a small, family owned business located in the heart of Conway, Arkansas. We purchase overstock, shelf pulls and store returns from many different liquidators around the United States so that we ...
查看更多內容
瀏覽商店聯絡

詳盡賣家評級

過去 12 個月的平均評級
說明準確
4.9
運費合理
5.0
運送速度
5.0
溝通
5.0

賣家信用評價 (9,612)

全部評級selected
正面
中立
負面