Chapter #2_Deep Learning.pdf....................

deep learning

1. Computer Science and IT | College of Computing |
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Dr. Mohammad Hujooj
Fahad bin Sultan University
College of Computing
Deep Learning

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Deep learning
Deeplearningispartofabroaderfamilyofmachine
learningmethodsbasedonArtificialNeuralNetworks(ANN)
withrepresentationlearning.Learningcanbesupervised,
semi-supervisedorunsupervised.
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Deep learning……..
Artificialneuralnetworks(ANNs)wereinspiredbyinformation
processinganddistributedcommunicationnodesinbiological
systems.ANNshavevariousdifferencesfrombiologicalbrains.
Specifically,artificialneuralnetworkstendtobestaticand
symbolic,whilethebiologicalbrainofmostlivingorganismsis
dynamic(plastic)andanalog.
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Deep learning……..……
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Definition
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Deeplearningisaclassofmachinelearningalgorithmsthatuses
multiplelayerstoprogressivelyextracthigher-levelfeaturesfromthe
rawinput.Forexample,inimageprocessing,lowerlayersmayidentify
edges,whilehigherlayersmayidentifytheconceptsrelevanttoa
humansuchasdigitsorlettersorfaces.

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Deep Learning Vs. Machine Learning Vs. AI:
An In-Depth Guide

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Deep Learning Vs. Machine Learning Vs. AI:
An In-Depth Guide…………
Self-driving cars
Touched-up selfies
Netflix recommendations
•Chatbots that write like people
•Virtual assistants that talk like friends
•Every last one of the billions of daily Google searches…

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Artificialintelligence(AI)isallaroundyou,andit’sonlygetting
morepervasive.Butifyoustartlookingintohowitworks,
you’llimmediatelyrunintoafewquestionsaboutthe
conceptssurroundingit:Whatisdeeplearningvs.machine
learning?Andhowdoartificialintelligence,machinelearning,
anddeeplearningrelatetooneanother?
Deep Learning Vs. Machine Learning Vs. AI:
An In-Depth Guide…………

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Therearesimpleanswerstothesequestionsaswellas
complexones,andthenthere’sthemathbehinditall,
whichissocomplicatedthatit’sprobablybesttosetaside
fornow.Atanylevelofunderstanding,theseanswersare
important—particularlyforbrandsandmarketers.Afterall,
AIincreasinglygovernsinteractionswithcustomers,as
illustratedbytheriseofvoiceAItechnologies.
Deep Learning Vs. Machine Learning Vs. AI:
An In-Depth Guide…………

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What do artificial intelligence, machine learning,
and deep learning mean?

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What do artificial intelligence, machine learning, and
deep learning mean?
Wikipedia’sdefinitionofArtificialintelligenceis
broadlyaccepted.Accordingtothesite,“AIis
intelligencedemonstratedbymachines.”Wikipedia
contraststhiswiththe“naturalintelligencedisplayedby
humansandanimals,whichinvolvesconsciousness
andemotionality.”Asforintelligenceitself,that’ssimply
anabilitytoobtaininformationanduseitadaptively.

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What do artificial intelligence, machine learning, and
deep learning mean?
•Machinelearningis“thestudyofcomputer
algorithmsthatimproveautomaticallythrough
experience,”sayscomputerscientistTomMitchell,who
literallywrotethebookonmachinelearning.

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What do artificial intelligence, machine learning, and
deep learning mean?
•Deeplearningisaformofmachinelearning
conducted(forthemostpart)throughdeepneural
networks(DNN).Thereareotherwaystoperform
deeplearning,butDNNsarefarandawaythemost
commoninpracticalusetoday.

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Withthesedefinitionsinmind,wecanaskourmain
question:What’stherelationshipbetweenmachine
learning,deeplearning,andAI?Deeplearningis
asubsetofmachinelearning,andmachine
learningisasubsetofAI.However,deep
learninghasbecomesodominantinAIcirclesthat,
whensomeonementionsAI,it’sextremelylikely
thatthey’realsotalkingaboutdeeplearning;you
canassumethatanydiscussionofAIisalsoa
discussionofdeeplearning(andthereforemachine
learning,too).
What do artificial intelligence, machine learning, and
deep learning mean?

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What is deep learning?
Inordertounderstanddeeplearning,youneedto
knowaboutdeepneuralnetworks.Thereare
othermachinelearningmodelsthatachievewhat
wecall“deeplearning,”butneuralnetworkshave
eclipsedalltheresttotheextentthatyoucan
safelyassumeanymentionofdeeplearningis
basedontheneuralnetworkmodel—somuchso
thataneffective(ifnotscientificallyaccurate)
definitionofdeeplearningcouldbe“machine
learningthroughdeepneuralnetwork
architecture.”

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TheNeuralNetworkcomputationmodelwas
inspiredbytheconnectionsofneuronswithinthe
humanbrain—butthat’sonlyaroughanalogy.When
yougetdowntothedetails,humanbrainsandneural
networksareextremelydifferent.Still,themetaphor
ishelpfulforunderstandingthebroadstrokesof
neuralnetworks:Neuralnetworksmimicthewaythe
humanbrainworkstoprocessinformation.
What is deep learning?

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Ourbrainslearnbyestablishingrepeatable
patternsofelectrochemicalconnectionsbetween
neurons.Aneuralnetworkdoessomethingsimilar.
Theneuralnetworks,widelyusedinthe1990s,
consistofthreelayersofnetworkedprocessors,or
artificialneurons:theinputlayer,ahiddenlayer,
andanoutputlayer.Eachneuronreceivesinput
data,performsanoperationonthatdata,and
exportstheresultsoftheoperationasaninputto
thenextprocessinglayer.
What is deep learning?..............

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Theseneuralnetworksarealsocalledmulti-layered
perceptrons(MLP),andtheyefficientlysolvedsome
ofthemostvexingproblemsoftheirera.Butwith
theincreasingavailabilityoflargerdatasets,and
longstrainsofresearchbreakingintopractice,
neuralnetworksevolvedalongsidethedawningera
ofBigData.
What is deep learning?..............

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How did deep learning go from theory to practical
application?
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There are three reasons deep learning took so long
to go from theory to everyday use.
1.Hardware.Whendeepneuralnetworksfirst
emerged,wedidn’thavehardwarethatwas
efficientenoughtotrainDNNs.Thatchangedwith
thedevelopmentofmoderngraphicsprocessing
units(GPUs)—thedevelopmentofwhichwas
hastenedalongbyvideogameconsoles,notthe
needsofacademics.TheGPUona$200video
gameconsolecanbeidealhardwarefortraining
complexDNNmodels—muchbetterthanevenan
advancedcentralprocessingunit,orCPU.

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How did deep learning go from theory to practical
application?……..
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2.Bigdata.Largedatasetsweren’tasavailablein
theearlydaysofneuralnetworks.Totrainacomplex
DNNmodelinastableway,youneedextraordinary
amountsofdata.IntheearlydaysofAI,thatdata
wasn’tavailable.Nowthereareeasilyaccessible
platformsthatallowresearcherstocollectbillions
andbillionsofdatapointseverysingleday.

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How did deep learning go from theory to practical
application?……..
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3.Deeplearningalgorithms.Mostimportantly,
scientistshadn’tyetdevisedthealgorithmsweuseto
keephighlycomplexDNNmodelsstableduring
training.Earlyalgorithmsledtounstablemodels,
whichweren’tdependableenoughforpracticaluse.
Thankstotheworkofenterprisingscientists,today’s
deeplearningalgorithmscantrainstableDNNmodels
toachieveconsistentresults.

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Assignment_Moodle
Suggest a system in your work that includes the use of
deep learning, with an explanation of the way in which
this system can be applied. You can use algorithms,
pseudo code, graphs.....etc.

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