Qhov sib txawv tseem ceeb ntawm neural network thiab kev kawm sib sib zog nqus yog tias neural network ua haujlwm zoo ib yam li cov neurons hauv tib neeg lub hlwb los ua ntau yam kev suav ua haujlwm sai dua thaum kev kawm tob yog hom tshwj xeeb ntawm kev kawm tshuab uas xyaum txoj kev kawm tib neeg siv tau kev paub.
Neural network pab tsim cov qauv kev kwv yees los daws cov teeb meem nyuaj. Ntawm qhov tod tes, kev kawm tob yog ib feem ntawm kev kawm tshuab. Nws pab txhim kho kev paub txog kev hais lus, kev paub cov duab, kev ua cov lus ntuj, cov lus pom zoo, bioinformatics thiab ntau ntxiv. Neural Network yog ib txoj hauv kev los siv kev kawm tob.
Neural Network yog dab tsi?
Cov neurons lom neeg yog qhov kev tshoov siab rau neural networks. Muaj ntau lab tus neurons nyob rau hauv tib neeg lub hlwb thiab cov ntaub ntawv txheej txheem los ntawm ib tug neuron mus rau lwm tus. Neural Networks siv qhov xwm txheej no. Lawv tsim ib lub computer qauv zoo ib yam li lub hlwb. Nws tuaj yeem ua cov haujlwm nyuaj ua haujlwm sai dua li ib txwm siv.
Daim duab 01: Neural Network thaiv daim duab
Nyob rau hauv lub neural network, cov nodes txuas rau ib leeg. Txhua qhov kev sib txuas muaj qhov hnyav. Thaum cov inputs rau cov nodes yog x1, x2, x3, … thiab cov hnyav sib xws yog w1, w2, w3, …
y=x1w1 + x2w2 + x3w3 + ….
Tom qab siv cov tswv yim nkag mus rau qhov ua kom muaj nuj nqi, nws muab cov zis tawm. Kev ua kom muaj nuj nqi tuaj yeem yog linear lossis sigmoid muaj nuj nqi.
Y=F(y)
Yog tias qhov tso zis no txawv ntawm qhov xav tau, qhov hnyav tau hloov kho dua thiab cov txheej txheem no txuas ntxiv mus txog thaum tau txais cov txiaj ntsig xav tau. Qhov kev hloov kho qhov hnyav no tshwm sim raws li cov txheej txheem backpropagation.
Muaj ob lub neural network topologies hu ua feedforward thiab tawm tswv yim. Feedforward networks tsis muaj cov lus teb rov qab. Hauv lwm lo lus, cov teeb liab tsuas yog ntws los ntawm cov tswv yim mus rau qhov tso zis. Feedforward tes hauj lwm ntxiv faib rau ib txheej thiab ntau txheej neural networks.
Network Types
Nyob rau hauv ib txheej tes hauj lwm, txheej input txuas mus rau cov zis txheej. Multi-layer neural network muaj ntau cov khaubncaws sab nraud povtseg ntawm cov txheej txheem nkag thiab cov txheej txheem tso tawm. Cov khaubncaws sab nraud povtseg yog hu ua cov txheej zais. Lwm hom network uas yog cov lus tawm tswv yim network muaj cov kev tawm tswv yim. Ntxiv mus, muaj peev xwm kis tau cov ntaub ntawv rau ob sab.
Daim duab 02: Multilayer Neural Network
Neural network kawm los ntawm kev hloov kho qhov hnyav ntawm kev sib txuas ntawm cov nodes. Muaj peb hom kev kawm, xws li kev kawm saib xyuas, kev kawm tsis saib xyuas thiab kev kawm ntxiv. Nyob rau hauv kev saib xyuas kev kawm, lub network yuav muab ib tug tso zis vector raws li input vector. Qhov no tso zis vector yog piv nrog qhov xav tau tso zis vector. Yog tias muaj qhov sib txawv, qhov hnyav yuav hloov kho. Cov txheej txheem no txuas ntxiv mus kom txog thaum cov khoom tso tawm tiag tiag nrog cov zis xav tau.
Hauv kev kawm tsis muaj kev saib xyuas, lub network txheeb xyuas cov qauv thiab cov yam ntxwv los ntawm cov ntaub ntawv nkag thiab kev sib raug zoo rau cov ntaub ntawv nkag los ntawm nws tus kheej. Hauv kev kawm no, cov tswv yim vectors ntawm hom zoo sib xws ua ke los tsim pawg. Thaum lub network tau txais tus qauv tawm tswv yim tshiab, nws yuav muab cov zis qhia txog cov chav kawm uas tus qauv nkag mus rau. Txoj kev kawm txhawb zog lees txais qee qhov kev tawm tswv yim los ntawm ib puag ncig. Tom qab ntawd lub network hloov qhov hnyav. Cov no yog cov txheej txheem los cob qhia cov neural network. Zuag qhia tag nrho, neural networks pab daws ntau yam teeb meem kev paub txog tus qauv.
Dab tsi yog kev kawm tob?
Ua ntej kev kawm tob, nws yog ib qho tseem ceeb los tham txog kev kawm tshuab. Nws muab lub peev xwm rau lub computer kawm yam tsis muaj programmed. Hauv lwm lo lus, nws pab tsim kev kawm tus kheej algorithms los txheeb xyuas cov ntaub ntawv thiab paub txog cov qauv los txiav txim siab. Tab sis, muaj qee qhov kev txwv yog kev kawm tshuab dav dav. Ua ntej, nws yog ib qho nyuaj rau kev ua hauj lwm nrog cov ntaub ntawv loj loj los yog cov txheej txheem loj heev ntawm cov khoom siv thiab cov khoom tawm. Nws kuj tseem yuav nyuaj rau kev tshem tawm cov yeeb yam.
Kev kawm tob daws cov teeb meem no. Nws yog hom tshwj xeeb ntawm kev kawm tshuab. Nws pab tsim kev kawm algorithms uas tuaj yeem ua haujlwm zoo ib yam li tib neeg lub hlwb. Kev sib sib zog nqus neural networks thiab cov kev sib txuas neural recurrent yog qee qhov kev kawm sib sib zog nqus. Lub network sib sib zog nqus neural yog Neural network nrog ntau txheej txheej zais. Cov kev sib txuas neural rov tshwm sim siv lub cim xeeb los ua cov txheej txheem ntawm cov khoom siv.
Dab tsi yog qhov txawv ntawm Neural Network thiab Deep Learning?
A Neural Network yog ib txoj haujlwm ua haujlwm zoo ib yam li cov neurons hauv tib neeg lub hlwb kom ua tau ntau yam kev suav ua haujlwm sai dua. Kev kawm tob yog ib hom kev kawm tshwj xeeb ntawm tshuab uas ua raws li txoj kev kawm uas tib neeg siv kom tau txais kev paub. Neural Network yog ib txoj hauv kev kom tau txais kev kawm tob. Ntawm qhov tod tes, Deep Leaning yog ib daim ntawv tshwj xeeb ntawm Tshuab Leaning. Qhov no yog qhov sib txawv tseem ceeb ntawm neural network thiab kev kawm tob
Summary – Neural Network vs Deep Learning
Qhov txawv ntawm neural network thiab kev kawm sib sib zog nqus yog tias neural network ua haujlwm zoo ib yam li cov neurons hauv tib neeg lub hlwb los ua ntau yam kev suav ua haujlwm sai dua thaum kev kawm tob yog hom tshwj xeeb ntawm kev kawm tshuab uas xyaum txoj kev kawm tib neeg siv kom tau txais kev paub.
