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008 170926s2018 maua b 001 0 eng
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082 0 0 _a006.3/1
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084 _aCOM004000
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090 _aQ 325.5
_b.S45 2018
100 1 _aSejnowski, Terrence J.
_q(Terrence Joseph),
_eauthor.
_9187029
245 1 4 _aThe deep learning revolution /
_cTerrence J. Sejnowski.
264 1 _aCambridge, Massachusetts :
_bThe MIT Press,
_c[2018]
300 _ax, 342 pages :
_billustrations (chiefly color) ;
_c24 cm
336 _atext
_btxt
_2rdacontent
337 _aunmediated
_bn
_2rdamedia
338 _avolume
_bnc
_2rdacarrier
504 _aIncludes bibliographical references (pages 285-319) and index.
505 0 0 _tPreface --
_gPart I.
_tIntelligence reimagined.
_tThe rise of machine learning ;
_tThe rebirth of artificial intelligence ;
_tThe dawn of neural networks ;
_tBrain-style computing ;
_tInsights from the visual system --
_gPart II.
_tMany ways to learn.
_tThe cocktail party problem ;
_tThe Hopfield net and Boltzmann machine ;
_tBackpropagating errors ;
_tConvolutional learning ;
_tReward learning ;
_tNeural information processing systems --
_gPart III.
_tTechnological and scientific impact.
_tThe future of machine learning ;
_tThe age of algorithms ;
_tHello, Mr. Chips ;
_tInside information ;
_tConsciousness ;
_tNature is cleverer than we are ;
_tDeep intelligence --
_gGlossary.
520 8 _aHow 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 enormous 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.
650 0 _aMachine learning.
_9187030
650 0 _aBig data.
_9187031
650 0 _aArtificial intelligence
_xSocial aspects.
_9187032
650 7 _aCOMPUTERS
_xDatabase Management
_xData Mining.
_2bisacsh
_9187033
650 7 _aArtificial intelligence
_xSocial aspects.
_2fast
_9187032
650 7 _aBig data.
_2fast
_9187031
650 7 _aMachine learning.
_2fast
_9187030
650 7 _aK�unstliche Intelligenz
_2gnd
_9187034
650 7 _aNeuronales Netz
_2gnd
_9187035
650 7 _aMaschinelles Lernen
_2gnd
_9187036
942 _2lcc
_cBOOK
907 _a49600