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

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Terrence J. Sejnowski 作者

MIT

译者

2018-6-22 出版日期

280 页数

$27.95 价格

Hardcover

丛书系列

9780262038034 图书编码

The Deep Learning Revolution 在线电子书图书标签: 人工智能 MIT AI learning Psychologia Deep 数学和计算机 2019

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发表于2024-11-21

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

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

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"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."

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The Deep Learning Revolution 在线电子书著者简介

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).

The Deep Learning Revolution 在线电子书图书目录

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

The Deep Learning Revolution 在线电子书图书描述

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.

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