Chii chinonzi neural network?

Network dzetsinga Ivo chishandiso chakakosha mumunda yehungwaru hwekugadzira uye kudzidza muchina. Sezvo tekinoroji ichifambira mberi, zvinoramba zvichikosha kuti unzwisise mashandiro avanoita uye kuti ndeapi masimba avainawo. Muchinyorwa chino, Isu tichaongorora kuti chii chaizvo chinonzi neural network uye kuti dzinoshandiswa sei kugadzirisa ruzivo uye kuita mabasa akaomarara. Kubva kusangano rako kuenda mashandisirwo ayo maitiro, isu tichaongorora mune ese akakodzera tekinoroji maficha eiyi inonakidza nzvimbo yekudzidza.

-Kusuma kune neural network

A neural network ndiyo computational model yakafuridzirwa nekushanda kwehuropi hwemunhu, iyo inoshandiswa kugadzirisa matambudziko kudzidza kwakaoma uye kuzivikanwa kwepateni. Iyo inoumbwa neakatevedzana ekugadzirisa mayuniti anonzi artificial neurons, ayo akabatana nemumwe kuburikidza nehuremu hwekubatanidza. Izvi zvinongedzo zvinogadziridzwa panguva yekudzidzira maitiro kuitira kukwidziridza modhi uye nekuvandudza kuita kwayo.

Iyo yakakosha kugona kweneural network kugona kwayo kudzidza uye kugadzirisa kubva kune yekuisa data. Munguva yechikamu chekudzidzisa, neural network inogadzirisa huremu hwehuremu hwekubatana pakati peeuroni kudzikisa mutsauko pakati pekubuda kwayo uye inotarisirwa kubuda. Sezvo maitiro ekudzidzisa achifambira mberi, iyo neural network inokwanisa kuona mapatani mune data rekuisa uye kuita kuti kugona uku kuishandisa kune nyowani data. Izvi zvinoibvumira kuita mabasa akadai sekucherechedzwa kwemifananidzo, kurongedza data kana kufanotaura kukosha.

A ⁢neural network yakarongwa muzvikamu, apo imwe neimwe layer inoumbwa neseti yemaneuroni uye yakabatana kune inotevera neyakayerwa kubatana. Iyo yekupinza layer inogamuchira data yekupinda uye inoiparadzira kuburikidza netiweki kusvika yasvika painobuda layer, iyo inoburitsa mhinduro yekupedzisira. Pakati peiyo yekuisa layer uye yekubuda layer, panogona kunge paine akavigwa akaturikidzana anobatsira neural network kudzidza maficha uye kumiririra data zvakanyanya. Iyo ⁤kudzidza maitiro⁤ kunoitwa pachishandiswa ⁤optimization algorithms, senge grediyent descent,⁤iyo inowedzera kana kuderedza huremu hwemakonisheni kuti kuderedze basa rekurasikirwa.

Mukupedzisa, neural network ndeye computational modhi inotevedzera kushanda kwehuropi hwemunhu kugadzirisa yakaoma maitiro ekudzidza uye matambudziko ekuzivikanwa. Nekugadzirisa huremu hwekubatanidza pakati peeuroni, neural network inogona kudzidza kubva kune yekuisa data uye kugadzirisa mapinduriro ayo. Yakarongwa kuita zvidimbu uye nerubatsiro rwekugadzirisa algorithms, neural network inogona kuita mabasa akadai sekucherechedzwa kwemufananidzo uye kukosha kwekufanotaura. Kushandiswa kwayo muminda yakadai se⁤ kugadzirisa mufananidzo, mushonga uye ungwaru hwekugadzira Vanozviita chishandiso chine simba mundima yetekinoroji.

-Neural network inoshanda sei?

A neural network imhando yemakomputa ⁢inofemerwa nekushanda kwehuropi hwemunhu. Inoumbwa nemayuniti akabatana anonzi neurons, ayo akafanana nemasero etsinga muuropi. Ruzivo rwunoyerera nemuneural network, uko yuniti yega yega inoita masvomhu anonzi activation function kugadzirisa uye kuendesa data kune anotevera akaturikidzana.

Muneural network, kuwirirana pakati pemayuniti ane huremu hunogadziriswa mukati mekudzidziswa. Aya huremu anomiririra kukosha kwekubatana kwega kwega mukugadzirisa ruzivo. Panguva yekudzidziswa, iyo neural network inodzidza kugadzirisa uremu uhwu kuitira kuti modhi igone kuita mamwe mabasa, sekuziva mufananidzo, kupatsanura data, kana kufanotaura.

Kushanda kweneural⁢network yakavakirwa ⁢pamusimboti wekudzidza kuburikidza nemhinduro. Panguva yekudzidziswa, network inodyiswa nedata rekuisa⁢ uye mibairo inowanikwa inofananidzwa ⁢inotarisirwa kukosha. Kuburikidza ne optimization algorithms, network inogadzirisa huremu hwekubatanidza kudzikisa mutsauko pakati pezvawanikwa uye ⁣ zvinokosha⁤ zvinotarisirwa. Iyi nzira inodzokororwazve kusvikira network yakwanisa kusvika padanho rinogamuchirwa rekururama.

- Architecture yeneural network

neural network ⁢Iyo muenzaniso wekombuta wakafuridzirwa nekushanda kwehuropi hwemunhu hunoshandiswa kugadzirisa matambudziko akaomarara. zvinobudirira. Mavakirwo ayo akavakirwa pane yakabatana seti yemanodhi, anozivikanwa seartificial neurons, anoshanda pamwechete kugadzira uye kutumira ruzivo. .

Mukati architecture yeneural network, kune marudzi akasiyana-siyana ezvikamu anoita mabasa chaiwo ⁢mu⁤ maitiro ekudzidza nekufanotaura. Iyo yekuisa layer ine basa rekugamuchira iyo data yekupinza uye kuitumira kune yakavanzika maseketi, uko kunoitwa zvakanyanya kugadzirisa. Aya akavigwa akaturikidzana akaumbwa neakawanda neurons uye ane basa rekuona mapatani uye maficha mune data. Pakupedzisira, iyo yekubuda layer ndipo panowanikwa mhedzisiro yeneural network.

Chimwe chezvinhu zvakakosha mu architecture yeneural network iko kushandiswa kwezviyereso uye⁤ activation⁢ mabasa. Huremu huremu hunopihwa kune hukama pakati peeuroni uye kuona kukosha kwekubatana kwega kwega mukugadzirisa ruzivo. Activation mabasa, kune rumwe rutivi, ane basa rekusava nemutsara mukubuda kwetiweki Aya mabasa anosuma kusiri-mutsara mune zvinobuda zveeuroni uye Vanobvumira network kuti idzidze uye kuita maitiro akaomarara mune data.

Muchidimbu, architecture yeneural network ‍ isimba remakomputa system rinoshandisa kubatanidza kweartificial neurons kugadzirisa matambudziko akaomarara. Kuburikidza nematanho anogadzirisa ruzivo rwekupinza uye kushandura uremu uye activation mabasa, neural network inogona kudzidza nekugadzirisa mapatani mu data Iyi nzira inopa kuita kwakasiyana-siyana uye kugona munzvimbo dzakasiyana siyana, senge kuziva inzwi, ⁢komputa kuona uye kuongororwa kwedata.

- Mhando dzeneural network

Mune ino post tichataura nezve akasiyana marudzi e-neural network. A neural network⁢ Ndiyo computational modhi yakafuridzirwa ne hurongwa hwetsinga biological. Inoshandiswa kugadzirisa matambudziko akaoma anoda kucherechedzwa kwepateni uye kudzidza muchina. Neural network inoumbwa nemanodhi akabatana anonzi artificial neurons, ayo akarongwa muzvikamu.

Kune akati wandei mhando dzeneural network,⁢ imwe neimwe yakagadzirirwa kugadzirisa akasiyana marudzi ematambudziko. Vamwe mhando dzeneural network Dzakakurumbira dzinosanganisira:

1. Feedforward neural network: Mune rudzi urwu rwetiweki, ruzivo runoyerera munzira imwe chete, kubva pachikamu chekuisa kusvika kune chekubuda Chinonyanyo shandiswa kurongedza uye matambudziko ekuzivikanwa kwepateni.

2. ⁤ Network dzetsinga dzinodzokororwa: Kusiyana nemafeedforward network, anodzokororwa neural network ane zvinongedzo zvinogadzira kutenderera. Izvi zvinovabvumira kuchengetedza ruzivo muchimiro chenyika dzakapfuura, izvo zvinoita kuti zvive zvakanaka kune matambudziko anosanganisira kutevedzana, sekuziva kutaura uye kududzira muchina.

3. Convolutional neural network: Manetiweki aya anoshanda mukugadzirisa data ine grid chimiro, senge mifananidzo kana masaini masaini. Ivo vanokwanisa kuburitsa akakodzera maficha kubva kudhata vachishandisa convolution layer, izvo zvinoita kuti zvinyatso shanda mukuona komputa nemabasa ekuzivikanwa kwechinhu.

Imwe neimwe yemhando idzi dzeneural network ine yayo zvakanakira nezvakaipira, ⁤uye zvakakosha kusarudza ⁢yakakodzera ⁤dambudziko chairo raunoda kugadzirisa.

-Zvinhu zvakakosha mune neural network

A network yetsinga imhando yemasvomhu inoumbwa neseti yakabatana ye artificial neurons. Aya ma<em>artificial neurons anofemerwa ne<em>biological neurons dzehuropi hwemunhu uye anoshandiswa kutevedzera kushanda kwehuropi hwekugadzira. Muneural network, artificial neuron yega yega inogamuchira akatevedzana ezvekupinda, inoita calculation neizvo zvinopinza, uye inoburitsa zvinobuda. Ichi chinobuda chakabatana sechipo kune mamwe artificial neurons, nekudaro kugadzira yakafanana uye yakagoverwa komputa nzira inobvumira kugadzirisa matambudziko akaomarara.

Zvinhu zvakakosha pane network neuronal ⁢ ndezvi:

1. Artificial neurons: Iwo ma basic processing units anogashira akatevedzana ezvekupinza uye anoburitsa zvinobuda. Imwe neimwe artificial neuron ine yakabatana activation function inotaridza maverengerwo azvinobuda zvichibva pane zvakatambirwa.

2. Synaptic uremu: Iwo manhamba manhamba anomiririra simba rekubatana pakati peartificial neurons. Huremu uhu hunotaridza pesvedzero iyo inobuda yeimwe artificial neuron ine pakupinza kweimwe artificial neuron. Huremu hweSynaptic hunogadziriswa panguva yekudzidza kweneural network kuti iwedzere kuita kwayo.

3. Network architecture: Zvinoreva kuumbwa uye kurongeka kwemaneuron ekugadzira uye kubatana kuri pakati pawo. Kune mhando dzakasiyana dzeneural network architectures, senge feedforward neural network, umo ruzivo rwunoyerera munzira imwe kubva kune yekupinza layer kusvika kune inobuda layer, kana recurrent neural network, umo Iwo makabatana anoumba zvishwe uye anobvumira ruzivo rwenguva pfupi kuti rugadziriswe.

Muchidimbu, neural network ndeye computational modhi yakavakirwa pane yakabatana artificial neurons, iyo inoshandiswa kutevedzera uropi hwemunhu uye kugadzirisa matambudziko akaomarara. Zvinhu zvakakosha muneural network ndeye artificial neurons, huremu hwe synaptic, uye magadzirirwo etiweki. Kugadziriswa kwezviyereso zvesynaptic uye kurongeka kwemaneuroni kunotarisisa kuita uye kugona kweneural network kudzidza nekugadzirisa matambudziko.

-Ndeapi maapplication ane neural network?

Iyo network dzetsinga vave chishandiso chine simba⁢ mumunda we ungwaru hwekugadzira. Manetiweki aya akagadzirirwa kutevedzera kushanda kwehuropi hwemunhu, achibvumira michina kudzidza uye kuita sarudzo nenzira yakafanana neiyo munhu angaite Asi mashandisiro anoita neural network?

Chimwe chezvishandiso zvinonyanya kushandiswa zveneural network kucherechedzwa kwepateni Kutenda nekugona kwavo kudzidza nekuziva zvimwe zvinhu mumaseti edata akaomarara, network idzi dzinogona kuona mapatani mumifananidzo, zvinyorwa, kutaura, uye ⁢mamwe marudzi edata.⁢ Izvi zvine zvakakosha muminda yakadai sekuona komputa, kuziva inzwi uye kuona hutsotsi.

Kumwe kushandiswa kwakakosha kweneural network kuri mumunda wekufanotaura uye kuongororwa kwedata. ⁢Manetiweki aya anogona kudzidziswa kuongorora huwandu ⁣ruzivo uye kuwana mapatani akavanzika⁤ kana mafambiro mu data. ⁢Izvi ⁢zvinonyanya kukosha munzvimbo ⁤sekufembera kwemamiriro ekunze, kutengeserana kwemari, uye mishonga,⁤uko kuongororwa chaiko kwemahombe ⁤maseti edata anogona kubatsira ⁤kuita sarudzo dzine ruzivo.

-Zvakanakira uye zvakaipira neural network

Neural network imhando yemuchina yekudzidza modhi inofemerwa nekushanda kwehuropi hwemunhu. Ivo vanoshandisa algorithms uye akabatana zvimiro zvemanodhi anonzi neurons kugadzirisa ruzivo uye kufanotaura. Imwe ye⁤ zvakanakira Chinhu chikuru cheneural network kugona kwavo kudzidza uye kugadzirisa kubva kune data, zvichivabvumira kuvandudza mashandiro avo nekufamba kwenguva. Izvi zvinovaita chishandiso chine simba ⁤ chekugadzirisa matambudziko akaomarara uye ⁣kuita mabasa⁣ akadai sekucherechedzwa kwemifananidzo, kugadzirisa yemutauro wechisikigo uye fungidziro yenguva.

Zvisinei, panewo zvikanganiso yakabatana nekushandiswa kweneural network. Chekutanga, dzinogona kudhura zvakanyanya uye dzakadzama computational, kunyanya kana uchishanda nemavhoriyamu makuru e data. Izvi zvinogona kudzikamisa mashandisirwo ayo pamidziyo ine mashoma zviwanikwa. Uyezve, neural network inogona kunetsa kududzira nekutsanangura nekuda kwekuoma kwazvo uye huwandu hukuru hwema paramita anofanirwa kugadziridzwa panguva yekudzidziswa. Izvi zvinogona kuunza kusavimbana uye kuita kuti kutorwa kwematekinoroji aya kunetse mune mamwe minda, semushonga kana mutemo.

Kunyangwe izvi zvisingabatsiri, neural network inoramba iri chishandiso chakakosha mumunda wekudzidza muchina. Kugona kwavo kushanda nedata rakaomarara uye kudzidza abstract mapatani kunoita kuti ive yakanakira kune dzakasiyana siyana dzekushandisa. Pamusoro pezvo, nekufambira mberi muhardware uye matekiniki ekudzidzisa, akanyanya kushanda uye anodudzira neural network ari kugadzirwa, izvo zvinogona kubatsira kukunda zvimwe zvipimo zvazvino. Muchidimbu, neural network ine zvakanakira nezvayakaipira, asi kugona kwavo kushandura nzira yatinoita nekunzwisisa ruzivo kunoita kuti ive chishandiso chakakosha munyika yehungwaru hwekugadzira.

-Mazano ekudzidzisa uye optimize neural network

A neural network Iyo imhando yemakomputa inokurudzirwa nekushanda kwehuropi hwemunhu. Iyo ine nhevedzano yealgorithms uye zvidimbu zveakabatana neuroni ⁢anoshanda⁢ pamwechete kugadzira ruzivo nekuziva ⁤matani. Kusiyana nechinyakare algorithms, neural network inogona kudzidza kubva kudhata uye kugadzirisa mashandiro avo sezvo rumwe ruzivo rwunopihwa.

Kudzidzira uye kugadzirisa neural network kunogona kuve kwakaoma, asi neiyo mazano akakodzera, unogona kuwana mhedzisiro yakakwana. Chekutanga pane zvese, zvakakosha kuve neseti yedata mhando yepamusoro uye yakakura zvakakwana kudzidzisa neural network. Iyo yakanyanya kusiyanisa uye inomiririra iyo data seti, zviri nani mhedzisiro ichava. Pamusoro pezvo, ⁢zvakakosha kufanogadzirisa iyo data nenzira kwayo, sekujairira nekuipatsanura mukudzidziswa⁢ uye seti yekuyedza.

Chimwe chinhu chakakosha isarudzo ye optimization algorithm zvakakodzera. Pane akati wandei sarudzo dziripo, senge yakakurumbira backpropagation algorithm, inogadzirisa huremu uye biases yeneural network kuderedza kukanganisa. Izvo zvakare zvinokurudzirwa kuti uedze neakasiyana hyperparameters, akadai seyero yekudzidza uye saizi yebatch, kuti uwane iyo yakakwana kumisikidzwa inobvumira iyo neural network kuchinjika nekukurumidza uye kuwana mhedzisiro iri nani. ⁤Uyezve, zvakakosha kuyeuka kuti kudzidzisa neural network inogona kuita iterative process, saka zvinokurudzirwa kugadzirisa nekuvandudza ma hyperparameters paunenge uchifambira mberi mukudzidziswa.

-Maitiro emangwana mumunda weneural network

A network yetsinga Iyo imhando yekombuta inokurudzirwa nekushanda kwehuropi hwemunhu Inoumbwa neseti yemayuniti anonzi neurons, ayo akabatana kune mumwe nemumwe kuburikidza nezvinongedzo kana zvinongedzo. Aya mabatanidzo akarongwa kuita zvidimbu, apo imwe neimwe layer inotaurirana neinotevera kuburikidza nemagetsi masaini. Iwo⁢ neural network Vane kugona kudzidza nekuvandudza mashandiro avo sezvavanopihwa rumwe ruzivo.

Iyo neural network Iwo akaratidzirwa kuve anoshanda zvakanyanya muakasiyana maapplication, anosanganisira kucherechedzwa kwekutaura, kuona komputa, kududzira muchina, uye ongororo yemanzwiro. Kubudirira kwavo kunokonzerwa nechikamu chikuru mukugona kwavo kubata uye kuenzanisira mapatani akaoma mu data, vachivaita maturusi ane simba ekugadzirisa ruzivo. Sezvo tekinoroji ichifambira mberi, mafambiro emangwana Mundima yeneural network, vanonongedza kune kuvandudzwa kweakakura uye akadzama network, inokwanisa kugadzirisa ari kuramba achinetsa uye kugadzirisa data. munguva chaiyo.

Imwe ye mafambiro emangwana Chinhu chinonyanya kunakidza mumunda weneural network ndiko kushandiswa kweanogadzira adversarial network (GANs). Aya ma network ane zvikamu zviviri: jenareta uye saruro. Jenareta inogadzira mifananidzo yekugadzira kana data, nepo musarura anoaongorora uye anoona kuti ndeyechokwadi here kana kuti manyepo. Kudzidziswa kwemanetiweki aya ⁣ kwakavakirwa ⁢pamakwikwi pakati pemapato ese, izvo zvinounza ⁣ ⁣ ⁣ kuvandudzwa nguva dzose kwekwaniso yejenareta kuburitsa ⁤ data rechokwadi. Iko kushandiswa kweGAN kunovimbisa kushandura minda senge chizvarwa chekugadzira zvemukati uye chokwadi chakawedzerwa.

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