The Deep Learning Revolution pdf epub mobi txt 電子書 下載 2024


The Deep Learning Revolution

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Terrence J. Sejnowski
MIT
2018-6-22
280
$27.95
Hardcover
9780262038034

圖書標籤: 人工智能  MIT  AI  learning  Psychologia  Deep  數學和計算機  2019   


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发表于2024-05-13

The Deep Learning Revolution epub 下載 mobi 下載 pdf 下載 txt 電子書 下載 2024

The Deep Learning Revolution epub 下載 mobi 下載 pdf 下載 txt 電子書 下載 2024

The Deep Learning Revolution pdf epub mobi txt 電子書 下載 2024



圖書描述

How deep learning -- from Google Translate to driverless cars to personal cognitive assistants -- is changing our lives and transforming every sector of the economy.

The deep learning revolution has brought us driverless cars, the greatly improved Google Translate, fluent conversations with Siri and Alexa, and enormus profits from automated trading on the New York Stock Exchange. Deep learning networks can play poker better than professional poker players and defeat a world champion at Go. In this book, Terry Sejnowski explains how deep learning went from being an arcane academic field to a disruptive technology in the information economy.

Sejnowski played an important role in the founding of deep learning, as one of a small group of researchers in the 1980s who challenged the prevailing logic-and-symbol based version of AI. The new version of AI Sejnowski and others developed, which became deep learning, is fueled instead by data. Deep networks learn from data in the same way that babies experience the world, starting with fresh eyes and gradually acquiring the skills needed to navigate novel environments. Learning algorithms extract information from raw data; information can be used to create knowledge; knowledge underlies understanding; understanding leads to wisdom. Someday a driverless car will know the road better than you do and drive with more skill; a deep learning network will diagnose your illness; a personal cognitive assistant will augment your puny human brain. It took nature many millions of years to evolve human intelligence; AI is on a trajectory measured in decades. Sejnowski prepares us for a deep learning future.

The Deep Learning Revolution 下載 mobi epub pdf txt 電子書

著者簡介

Terrence J. Sejnowski holds the Francis Crick Chair at the Salk Institute for Biological Studies and is a Distinguished Professor at the University of California, San Diego. He was a member of the advisory committee for the Obama administration's BRAIN initiative and is President of the Neural Information Processing (NIPS) Foundation. He has published twelve books, including (with Patricia Churchland) The Computational Brain (25th Anniversary Edition, MIT Press).


圖書目錄


The Deep Learning Revolution pdf epub mobi txt 電子書 下載
想要找書就要到 小哈圖書下載中心
立刻按 ctrl+D收藏本頁
你會得到大驚喜!!

用戶評價

評分

god damn crazy, wonderful articles!respect!

評分

"Neural nets are often too complex to explain their decisions in relatable terms, they can perpetuate social discrimination if trained on biased data, and they can be used for autonomous weapons that might become trigger-happy. Granted, humans are also opaque, unfair and ornery."

評分

god damn crazy, wonderful articles!respect!

評分

與其說這本書迴顧瞭半個多世紀來深度學習的發展,不如說這是一本深度學習和腦神經科學的科普書。深度學習涉及的每個領域基本都介紹瞭,當然部分章節不是特彆深入,比如第十七章關於 NLP 的內容。總體來說,是一本非常棒的科普書,適閤快速瞭解 AI 再過去半個多世紀的發展曆程。讀完再也不會被一知半解的媒體忽悠瞭。

評分

Nice overall coverage and cadence. Machine learning, neuroscience, psychology and education all converged here.

讀後感

評分

当下,人工智能已经成为新一轮产业变革的核心驱动力,在全球范围内蓬勃兴起,正在深刻改变人们的生产生活方式,对世界经济、社会进步和人类生活产生极为深远的影响。掀起这股变革大潮的,正是大名鼎鼎的深度学习技术。这项技术可以追溯到人工智能诞生的20世纪50年代,虽然经历...  

評分

人工智能元年:2016? 对于一个普通大众而言,2016无疑是人工智能元年:阿尔法狗(AlphaGO)对战韩国围棋界18次世界冠军获得者李世石。其后,2017年,阿尔法狗化生Master横扫网络围棋服务器,5月,阿尔法狗连胜柯洁三场。就从那个时候,我身边不少患有中年焦虑症的朋友又有了新...  

評分

人工智能元年:2016? 对于一个普通大众而言,2016无疑是人工智能元年:阿尔法狗(AlphaGO)对战韩国围棋界18次世界冠军获得者李世石。其后,2017年,阿尔法狗化生Master横扫网络围棋服务器,5月,阿尔法狗连胜柯洁三场。就从那个时候,我身边不少患有中年焦虑症的朋友又有了新...  

評分

看到王勇老师的朋友圈的推荐买了这本书,在人工智能深度学习领域炽热的今天读这本书倒比较应景,约汉森顿,杨卫坤和约书亚获得了2018年的图灵奖,为深度学习在人工领域的高潮添加了一颗明珠。作为和约汉森顿交流合作颇多的作者而言,出这本书颇合时宜。 去年读了一本人工智能诸...  

評分

作者是深度学习领域的领军人物,本书可以算是作者写的人工智能简史,涉及到作者参与的一些项目,作者跟许多业内知名科学家都有学术交往。 书中涉及到一些人工智能算法的基本原理,没学过高数、没有编程基础的读者恐怕是比较难看懂的。不过看不懂可以跳过去,至少一些学术发展的...  

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