Chii chinonzi Artificial Neural Networks?

Chii chinonzi Artificial Neural Networks?

Artificial Neural Networks (ANN) mhando dzemakomputa dzinofemerwa nekushanda kwehuropi hwemunhu. Aya masisitimu ekugadzirisa ruzivo, akavakirwa paalgorithms uye matekiniki esvomhu, ave chimwe chezvishandiso zvine simba mumunda. yehungwaru hwekugadzira. Kugona kwayo kudzidza uye kugadzirisa kubva kumienzaniso yakapihwa kwakatungamira kufambiro mberi kwakakosha munzvimbo dzakaita sekucherechedzwa kwepateni, kupatsanurwa kwedata, kufanotaura kwemhedzisiro, uye kunyangwe kuita sarudzo.

Kusiyana nemaitiro echinyakare algorithms, maANN haatevedzere yakafanotsanangurwa zvine musoro kutevedzana, asi kuti anoshanda kuburikidza neyakafanana uye yakagoverwa chimiro, ichibatanidza akawanda akabatana node anonzi "artificial neurons." Imwe neimwe yeiyi neuroni inokwanisa kugadzirisa ruzivo rwainogamuchira, kuita masvomhu uye kuendesa mhedzisiro kune dzimwe neuroni dziri pedyo, zvichibvumira kubatana kukuru uye panguva imwe chete kugadzirisa mukati mehurongwa.

MaANN anoumbwa nezvikamu zvakasiyana, imwe neimwe iine seti chaiyo yemaneuroni. Yekutanga layer, inozivikanwa seyekuisa layer, inogamuchira uye inogadzirisa yekutanga data yekuisa. Kuburikidza nekubatana kwe synaptic, ruzivo runoyerera kune zvidimbu zvakavanzwa, umo kugadzirisa uye kubviswa kwezvinhu zvakakosha kunoitika. Chekupedzisira, iyo yekubuda layer inopa mhedzisiro inowanikwa nehurongwa.

Kushanda kweANN kwakavakirwa pakupihwa kwehuremu kune hukama pakati pema neuron, ayo anoona kukosha kwekubatana kwega kwega. Aya uremu anogadziridzwa zvakapetwa panguva yehurongwa hwekudzidzisa maitiro, uchishandisa algorithms yekudzidza. Nenzira iyi, iyo ANN inodzidza kukwenenzvera kuita kwayo uye kuburitsa mhinduro dzakanyatsojeka sezvo ichiratidzwa kune mimwe mienzaniso uye data.

Pasinei nekuoma kwavo, maANN ari kuwedzera kushandiswa uye kudzidza munzvimbo dzakasiyana-siyana dzakadai semushonga, marobhoti, kuona komputa, kugadzira mutauro wechisikigo uye indasitiri yekufambisa, pakati pezvimwe. Kugona kwayo kugadzirisa huwandu hukuru hwe data uye kuwana mapatani akavanzika kwakashandura dzidziso dzakawanda uye kufambisa hutsva hwetekinoroji.

Muchidimbu, Artificial Neural Networks inomiririra nzira inonakidza yeku ungwaru hwekugadzira, zvichiita kuti michina idzidze nenzira yakafanana nemadzidzisiro anoita vanhu. Yavo yakafanana, inogadzirisa chimiro yakavakirwa pahuremu hwekubatanidza inoita kuti ive chishandiso chakakosha chekugadzirisa matambudziko akaomarara uye kugadzirisa mashandiro eakawanda tekinoroji maapplication.

1. Nhanganyaya kune Artificial Neural Networks

Artificial Neural Networks imodhi yekombuta yakafemerwa nehuropi hwemunhu, yakagadzirirwa kutevedzera maitiro ekudzidza emaneuroni. Aya ma network anoshandiswa munzvimbo dzakasiyana siyana sekuzivikanwa kwepateni, kufanotaura kwedata, kugadzirisa kwemifananidzo uye kutonga kwehurongwa. Ivo vanonyanya kubatsira mumatambudziko akaomarara anoda parallel processing uye kuchinjika.

Kushanda kweArtificial Neural Networks kunobva pakubatana kwemanode kunonzi artificial neurons kana mayunitsi ekugadzirisa. Aya mayunitsi akaiswa muzvikamu uye chimwe nechimwe chazvo chinoita mashandiro emasvomhu achishandisa ruzivo rwakagamuchirwa kubva kuzvikamu zvakapfuura. Kubatana kwega kwega pakati pemayuniti kune huremu hwakabatana hunotaridza kukosha kwekubatana ikoko mukuita kudzidza.

Kune akasiyana marudzi eArtificial Neural Networks, senge feedforward network, inodzokororwa network uye convolutional network. Rudzi rwega rwega rune hunhu hunoita kuti vakwanise kuita mabasa akasiyana. Pamusoro pezvo, kune maalgorithms ekudzidza anobvumira aya network kuti adzidziswe kucherechedzwa kwepateni kana kugadzirisa matambudziko chaiwo.

Muchidimbu, Artificial Neural Networks chishandiso chine simba chekugadzirisa matambudziko akaomarara anoda kuenderana kugadzirisa uye kugona kugadzirisa. Kushanda kwayo kunobva pakubatana kweartificial neurons uye kugoverwa kwezviyero kune izvi zvinongedzo, izvo zvinobvumira kudzidza maitiro. Naizvozvo, kushandiswa kwayo kwakafara uye kunobva pakuzivikanwa kwepateni kusvika pakugadzirisa mufananidzo.

2. Nhoroondo pfupi yeArtificial Neural Networks

Artificial Neural Networks (ANN) imhando yemasvomhu uye yekombuta inofemerwa nepakati tsinga dzezvipenyu, iyo inoumbwa neakabatana neuroni. Pfungwa yekushandisa artificial neural network yakabuda mu1940s, asi hazvina kusvika kuma1980s pavakatanga kuvandudzwa zvakanyanya.

Chinangwa chikuru cheartificial neural network ndechekutevedzera kushanda kwehuropi hwemunhu kugadzirisa matambudziko akaomarara. zvinobudirira. Manetiweki aya anoumbwa nezvikamu zvemaneuron akabatana, uko neuron yega yega inogamuchira mapoinzi, inoita maoparesheni neaya ekuisa uye inoburitsa inobuda inoshanda sekuisa kune inotevera neuron.

Kuti uite izvi, artificial neural network anoshandisa muchina kudzidza algorithms anogadzirisa huremu hwekubatana pakati peeuroni panguva yechikamu chekudzidzisa, kuti network idzidze kuita mabasa anodiwa. Mimwe mienzaniso Zvishandiso zveartificial neural network zvinosanganisira kucherechedzwa kwekutaura, kuona chitsotsi, kuongororwa kwekurapa uye kufanotaura kwemamiriro ekunze.

Muchidimbu, artificial neural network ndiyo computational modhi yakafemerwa nehuropi hwemunhu inobvumira kugadzirisa matambudziko akaomarara kuburikidza nekushandisa muchina kudzidza algorithms. Manetiweki aya anoumbwa nezvikamu zveeurons akabatana, anogadzirisa uremu hwawo panguva yekudzidziswa kuti adzidze kuita mamwe mabasa. Chishandiso chayo chinovhara nzvimbo dzakasiyana siyana, kubva pakuzivikanwa kwezwi kusvika kukufanotaura kwemamiriro ekunze. Artificial neural network chishandiso chine simba chekuongorora uye kugadzirisa data!

3. Mamiriro uye kushanda kweArtificial Neural Networks

Artificial Neural Networks (ANNs) imhando dzemakombuta dzakavakirwa pachimiro uye kushanda kwehurongwa hwetsinga dzevanhu kugadzirisa matambudziko akaomarara. nzira inoshanda. Manetiweki aya anoumbwa nemayuniti ekugadzirisa anonzi artificial neurons uye akarongwa kuita zvidimbu zvakabatana zvinobvumira kufamba kweruzivo.

Iyo yakakosha chimiro cheANN inoumbwa neiyo yekuisa layer, imwe kana anopfuura yakavanda layer, uye yekubuda layer. Neuron yega yega mune imwe layer inobatana nemaneuron muchikamu chinotevera kuburikidza nehuremu hwekubatanidza. Kushanda kweANN kunoenderana nekugadziriswa kwemasaini ekuisa kuburikidza neaya akaremerwa kubatanidza uye kushandiswa kweiyo activation basa kuona kubuda kweneuron yega yega.

Kuti unzwisise zvirinani mashandiro anoita maANN, zvakakosha kuziva mhando dzakasiyana dzemanetiweki aripo, senge feedforward network uye anodzokororwa network. Uyezve, zvakakosha kuti unzwisise maalgorithms ekudzidza anoshandiswa mumaANN, akadai sekudzidza kwakatariswa uye kudzidza kusingatarisirwe. Aya maalgorithms anobvumira huremu hwekubatana pakati pemaneuron kuti agadziriswe kuitira kuti ANN ikwanise kudzidza nekuita zvakazara kubva kudhata rekudzidzisa.

4. Mhando dzeArtificial Neural Networks dzinoshandiswa nhasi

Parizvino, kune akati wandei marudzi eartificial neural network anoshandiswa mundima yeartificial intelligence uye kudzidza muchina. Manetiweki aya anokwanisa kutevedzera kushanda kwemaneuroni muuropi hwemunhu, achibvumira kugadziridzwa kweruzivo rwakaoma uye kuita sarudzo zvichienderana nematanho uye data.

Imwe yemhando dzakajairika dzeartificial neural network ndeye feed-forward neural network, inozivikanwawo semberi yekuparadzira neural network. Iyi network ine yekupinza layer, imwe kana kupfuura yakavanda layer, uye yekubuda layer. Ruzivo rwunoyerera negwara rimwe chete, kubva pachikamu chekupinza kuenda kune chekubuda, pasina mhinduro. Inonyanya kukosha pakuronga uye kucherechedzwa kwepateni.

Imwe mhando inoshandiswa zvakanyanya yeneural network ndeye recurrent neural network (RNN). Kusiyana netiweki yekudyisa-mberi, maRNN ane mafeed-forward akabatana anobvumira ruzivo kuti rwugadziriswe muzvishwe. Izvi zvinovaita kuti vanyanyokodzera mabasa anosanganisira kutevedzana, sekugadzirisa zvinyorwa uye ongororo yenguva. Uyezve, maRNN anokwanisa kudzidza kutsamira kwenguva refu, zvichiita kuti anyatsoshanda kumatambudziko enguva pfupi.

5. Kudzidza algorithms muArtificial Neural Networks

MuArtificial Neural Networks, maalgorithms ekudzidza anoita basa rakakosha mukudzidzisa uye kugadzirisa zvakanaka kushanda kwetiweki. Aya maalgorithms anobvumira iyo neural network kudzidza kubva kune yekuisa data uye kuita fungidziro kana kupatsanura zvichienderana neruzivo rwakadzidzwa. Pazasi pane matatu ekudzidza algorithms anoshandiswa zvakanyanya muartificial neural network.

1. Back Propagation Algorithm: Iyi algorithm inowanzoshandiswa mu multilayer neural network. Inosanganisira maitiro ekudzokorora umo mutsauko uripo pakati pekubuda chaiko kwetiweki uye zvinotarisirwa zvinobuda zvinoverengerwa, uye kukanganisa uku kunodzoserwa kumashure kuburikidza neakavanzika akaturikidzana kuti agadzirise huremu uye kusarura kwemaneuroni. Iyi nzira inodzokororwa kusvikira mambure asvika pamamiriro ekugadzirisa, nokudaro kuderedza kukanganisa kwekufanotaura.

2. Stochastic Gradient Descent (SGD) Algorithm: Iyi algorithm inoshandiswa kudzidzisa neural network nemaseti makuru e data. Panzvimbo pekuverenga zvigadziriso kune huremu uye kusarura uchishandisa yese yekudzidziswa seti, SGD inoverengera izvi zvigadziriso zvemuenzaniso mumwe chete wekudzidzisa panguva, inosarudzwa chero. Izvi zvinobvumira kukurumidza uye kunoshanda kudzidziswa, kunyanya kana uine yakakura data.

3. Maximum Likelihood Algorithm: Iyi algorithm inoshandiswa kudzidzisa neural network muzvikamu zvemabasa. Izvo zvakavakirwa pane zano rekuwedzera mukana wekuti fungidziro yetiweki ndeyechokwadi, zvichipihwa mazita anozivikanwa ekudzidzisa. Kuti uite izvi, basa rekurasikirwa rinoshandiswa rinoranga zvisizvo kufanotaura uye network parameter inogadziriswa kuti ideredze kurasikirwa uku. Iyo yakanyanya mukana algorithm inoshandiswa zvakanyanya mumaneural network kune bhinari uye multiclass classification matambudziko.

Muchidimbu, iwo akakosha yekudzidziswa uye kugadziriswa kwemanetwork aya. Iyo backpropagation algorithm, stochastic gradient descent, uye yakanyanya mukana algorithm ingori mienzaniso mishoma yemaalgorithms anoshandiswa mundima iyi. Neruzivo rwakakwana uye mashandisirwo eaya algorithms, zvinokwanisika kugadzira neural network inokwanisa kudzidza nekuita fungidziro mumatambudziko akasiyana siyana.

6. Zvikumbiro zveArtificial Neural Networks munzvimbo dzakasiyana

Artificial Neural Networks (ANNs) yakaratidza kuve chishandiso chakakosha muzvikamu zvakasiyana nekuda kwekugona kwavo kudzidza uye kugadzirisa kubva kudata. Aya manetwork, akafuridzirwa nekushanda kwehuropi hwemunhu, akawana mashandisirwo mundima dzakasiyana semushonga, mainjiniya uye sainzi yedata.

Mukurapa, maANN akashandiswa kuongorora zvirwere, kufanotaura fungidziro yevarwere, uye kuwana mapatani akavanzika mune data rekiriniki. Semuyenzaniso, maRNA akagadzirwa anogona kuona gomarara padanho rekutanga kubva pamifananidzo yekurapa kana genetic analysis. Pamusoro pezvo, manetwork aya anogona kuona mapatani mumaseti makuru edata rezvokurapa uye kubatsira vanachiremba kuita sarudzo dzine ruzivo nezvekurapa varwere.

Muinjiniya, maANN akashandiswa kugadzirisa kudzora kwakaoma uye matambudziko ekugadzirisa. Semuyenzaniso, neural network yakagadziridzwa kudzora marobhoti mukuchinja nharaunda, kuvandudza simba resimba rezvivakwa, uye kukwidziridza mashandiro ekugadzira masisitimu. Aya manetwork, akadzidziswa nehuwandu hwakawanda hwe data, anogona kudzidza yakaoma masvomhu modhi uye kugadzira mhinduro dzinoshanda kumatambudziko einjiniya.

7. Zvinetso uye zvisingakwanisi zveArtificial Neural Networks

Artificial Neural Networks (ANNs) chishandiso chine simba mumunda wekudzidza kwemichina uye nehungwaru hwekugadzira. Zvisinei, havasi vasina matambudziko neganhuriro. Kunzwisisa zvipingamupinyi izvi kwakakosha kuita nzira dzinovandudza mashandiro uye kushanda kweANN mumashandisirwo akasiyana. Pazasi pane mamwe ematambudziko akajairika uye zvisingakwanisi.

1. Kushaikwa kwedata: MaANN anoda huwandu hwakakura hwe data kudzidzisa uye kuita zvakazara nemazvo. Mune zvimwe zviitiko, zvinogona kunetsa kuwana yakakwana yemhando data kudzidzisa network zvinobudirira. Izvi zvinogona kutungamirira kumatambudziko ekuwandisa uye kushayikwa kwekugona kutora kuoma kwechokwadi kwedambudziko. Kudzikamisa dambudziko iri, nzira dzekuwedzera data senge kutenderera, kupenengura, uye kudzoreredza mapikicha, pamwe nekutamisa nzira dzekudzidza, dzinogona kushandiswa kuwedzera ruzivo rwakawanikwa kubva kumabasa akafanana.

2. Kutuka kwedambudziko re dimensionality: Sezvo huwandu hwezvimiro kana zvinosiyana museti yedata zvichiwedzera, maANN anogona kusangana nematambudziko mukutora hukama hune chinangwa uye hunoenderana. Izvi zvinokonzerwa nekutukwa kwehumwe hukuru, hunosanganisira kuparadzira data munzvimbo yepamusoro-soro. Kukwira dambudziko iri, kusarudzwa kwechimiro, kuderedzwa kwedimensionality uye data normalization matekiniki anogona kushandiswa.

3. Computational nguva uye mari: Kudzidzira uye kuongorora ANN kunogona kuda yakawanda yenguva uye computational zviwanikwa. Izvi zvinogona kunetsa, kunyanya kana uchishanda nemaseti makuru edata kana uchida mhinduro munguva chaiyo. Kugadzirisa nguva yecomputing uye mutengo idambudziko rakakura kana uchishandisa maANN mune zvinoshanda maapplication. Izvi zvinogona kuwanikwa kuburikidza nekugadzira algorithms ekudzidza anobudirira, uchishandisa nzira dzekufananidza, uye kusarudza akakodzera network ekuvaka kwedambudziko riripo.

Pasinei nezvipingamupinyi izvi uye zvisingakwanisi, maANN anoramba ari chishandiso chakakosha mumunda wehungwaru hwekugadzira. Kunzwisisa nekugadzirisa zvipingamupinyi izvi kunotitendera kushandisa zvizere kugona kweANN uye kukunda zvatisingakwanisi. Kuburikidza nekushandiswa kwakaringana kwehunyanzvi nemaitiro, izvo zvakaipa zvinokonzeresa zvinogona kudzikiswa uye mabhenefiti ayo aya network anogona kupa munzvimbo dzakasiyana dzekushandisa anogona kukwidziridzwa.

8. Zvakanakira uye zvisingabatsiri zveArtificial Neural Networks

Artificial neural networks (RNN) ndiwo masisitimu ehungwaru anoedza kutevedzera kushanda kwehuropi hwemunhu. Manetiweki aya anoumbwa neakawanda ekugadzirisa mayuniti anonzi neurons, ayo akarongwa kuita akabatana akaturikidzana kuti agadzirise uye aongorore huwandu hukuru hwe data. Pazasi pane akati wandei:

Zvakanakira:

1. Kudzidza kugona: MaRNN ane kugona kudzidza akazvimirira kuburikidza nekuenderera mberi nemhinduro. Izvi zvinoreva kuti vanogona kuchinjika kune data nyowani uye kugadzirisa huroyi hwavo nekuita nekufamba kwenguva.

2. Kunyatsogadziriswa kwemashoko akaoma: RNNs dzakaratidza kuva dzakanyanya kushanda mukugadzirisa mavhoriyamu makuru e data yakaoma, semifananidzo, zvinyorwa kana zviratidzo. Kugona kwavo kuziva mapatani uye kuita ongororo yekufungidzira kunoita kuti ive chishandiso chine simba chekushandisa kwakasiyana.

3. Kukanganisa kushivirira uye kusimba: Nekuda kwechimiro chadzo mumatanho akabatana, maRNN ane kugona kubhadhara nekugadzirisa zvikanganiso mu data rekuisa. Izvi zvinovabvumira kuti vawedzere kukanganisa kukanganisa uye kupa kusimba kukuru mumamiriro ezvinhu apo data haina kukwana.

Zvakashata:

1. Inoda huwandu hukuru hwe data: Kuti RNN idzidze uye ive yakazara nemazvo, inoda huwandu hukuru hwe data yekudzidziswa. Kana pasina mienzaniso yakakwana yekudzidzisa iripo, mashandiro etiweki anogona kukanganisika.

2. Kunonoka kudzidziswa uye nguva yekuuraya: Kudzidzira maRNN kunogona kuita kunonoka uye kudhura kwemakomputa, kunyanya kana zvasvika kune yakadzika network ine akawanda akaturikidzana. Uyezve, nguva yekuuraya yeRNN inogona zvakare kureba kana ichienzaniswa nedzimwe nzira dzekudzidza muchina.

3. Kushaya kududzira: Kunyangwe maRNN achikwanisa kuita mabasa nemazvo, maitiro avo ekuita sarudzo kazhinji haagone kududzirwa zviri nyore nevanhu. Izvi zvinoita kuti zviome kunzwisisa kuti fungidziro yakapihwa kana mhedzisiro yasvika sei, izvo zvinogona kudzikisira kushanda kwayo mune mamwe mamiriro akajeka.

Muchidimbu, Artificial Neural Networks inopa akawanda mabhenefiti, senge kugona kwavo kudzidza, kugona mukugadzirisa data rakaoma uye kusimba kwavo. Nekudaro, ivo vanewo zvakaipira, sekuda kwehuwandu hukuru hwe data yekudzidziswa, kudzidziswa kwenguva refu uye nguva dzekuuraya, uye kushaikwa kwekududzira mukuita sarudzo. Nekufunga uku mupfungwa, maRNN chishandiso chakakosha mumunda wehungwaru hwekugadzira, asi kuita kwavo kunofanirwa kutsigirwa nekunyatsoongorora uye kufunga nezve izvi. zvakanakira nezvakaipira.

9. Kuenzanisa pakati peArtificial Neural Networks uye uropi hwemunhu

Artificial neural network imhando dzemakomputa dzakagadzirirwa kutevedzera kushanda kwehuropi hwemunhu. Kunyangwe manetwork aya achikwanisa kuita mabasa akaomarara ekudzidza uye maitiro ekuzivikanwa, pane misiyano yakakosha pakati peartificial neural network nehuropi hwemunhu.

Chekutanga, artificial neural network anoumbwa neakatevedzana akabatana ekugadzirisa mayunitsi anonzi artificial neurons. Aya ma neurons anogashira masaini ekuisa akaremerwa, anoagadzirisa uchishandisa activation basa, uye kutumira chiratidzo chinobuda. Kusiyana nehuropi hwemunhu, uko maneuron ane hunyanzvi uye biological, artificial neurons zvikamu zvemasvomhu zvinoita masvomhu.

Mumwe mutsauko wakakosha inzira yekudzidzira neural network. Manetiweki aya anodzidza kuburikidza nemaitiro anonzi kudzidziswa, apo anounzwa neseti yedata rekuisa uye huremu hwekubatana pakati pema neuron anogadziridzwa kuti kuderedze mutsauko pakati pezvinotarisirwa kubuda uye kubuda chaiko. Kune rumwe rutivi, uropi hwomunhu hunodzidza kuburikidza nemaitiro akaoma zvikuru uye ane simba, anosanganisira kupindirana kwemabhiriyoni eeuroni uye synaptic connections.

Muchidimbu, kunyangwe artificial neural network aratidza kuve maturusi ane simba munzvimbo dzakadai kuziva inzwi, kuona kwekombiyuta uye kushandiswa kwemutauro wechisikigo zvichiri kure nekufananidza kukwanisa uye kushanda kwehuropi hwemunhu. Sezvo tsvakiridzo inofambira mberi uye kushanda kwehuropi kuri kunzwisiswa zviri nani, kufambira mberi kwakakosha kungangoitwa mukugadzira neural network yakafanana nehuropi hwemunhu.

10. Zvishandiso uye mitauro yekuronga kugadzira Artificial Neural Networks

Mukati memunda wehungwaru hwekugadzira, artificial neural network chishandiso chakakosha kugadzirisa uye kuongorora huwandu hukuru hwe data. Kugadzira artificial neural network, zvinodikanwa kuve nemidziyo yakakodzera uye mitauro yekuronga. Pazasi pane dzimwe sarudzo dzinoshandiswa zvakanyanya nhasi:

• TensorFlow: Iyi raibhurari yakavhurwa sosi yakagadziridzwa neGoogle ndeimwe yeanonyanya kufarirwa pakushandisa neural network. Inobvumira mamodheru kukudziridzwa mumitauro yakaita sePython kana Java, uye inopa akasiyana siyana ezvishandiso uye mabasa ekudzidziswa uye kuongororwa kweartificial neural network.
• Keras: Iyi iAPI yepamusoro-soro inomhanya pamusoro peTensorFlow. Inonyatsozivikanwa nekureruka kwekushandisa uye kugona kwayo kugadzira neural network nekukurumidza uye nyore. Keras inoenderana nePython uye inokutendera iwe kuti uvake mamodheru uchishandisa akafanotsanangurwa kana mabhuroko etsika.
• PyTorch: Iyi raibhurari yakavhurika sosi yekudzidza muchina, yakagadziridzwa neFacebook, inopa inochinjika chikuva chekuvandudza eartificial neural network. PyTorch inobvumira vanogadzira mapurogiramu kushandisa zvakajairika Python maturusi uye inopa intuitive interface yekuvaka uye kudzidzisa modhi.

Pamusoro pezvisarudzo izvi, kune mamwe akawanda maturusi uye mitauro yekuronga inowanikwa pakuvandudza eartificial neural network. Mamwe acho anosanganisira Caffe, Theano, MATLAB, uye scikit-dzidza, imwe neimwe iine yayo maficha uye maitiro. Zvakakosha kuongorora zvinodiwa uye zvinodiwa zvepurojekiti usati wasarudza chimbo chakakodzera uye mutauro.

Muchidimbu, kuve nematurusi akakodzera uye mitauro yekuronga kwakakosha pakuvandudza kunobudirira kweartificial neural network. TensorFlow, Keras, uye PyTorch ndedzimwe sarudzo dzakakurumbira dzinopa akasiyana siyana maficha uye zvivakwa. Zvisinei, zvakakoshawo kuongorora sarudzo dzakasiyana zvichienderana nezvinodiwa zvepurojekiti imwe neimwe. [END-HTML-MARKUP]

11. Kukosha kweArtificial Neural Networks muuchenjeri hwekugadzira

Artificial Neural Networks (ANN) chikamu chakakosha chehungwaru hwekugadzira (AI). Manetiweki aya akagadzirirwa kutevedzera kushanda kwehuropi hwemunhu uye anokwanisa kudzidza nekugadzirisa kuburikidza neruzivo. Kukosha kwayo kuri mukukwanisa kwayo kugadzirisa matambudziko akaomarara, kufanotaura uye kuita sarudzo zvichienderana nehuwandu hwakawanda hwe data.

Imwe yemabhenefiti makuru eANN kugona kwavo kuziva mapatani uye kutora ruzivo rwakakodzera kubva kumaseti makuru edata. Izvi zvinobvumira michina kuona mafambiro, kuronga ruzivo uye kuita sarudzo dzakanyanya. MaANN anoshandawo zvakanyanya mukuzivikanwa kwekutaura, kugadzirisa mutauro wechisikigo, uye kuona komputa.

Kuti uwane zvakanyanya kubva kumaANN, zvakakosha kuve nedata rakakwana uye nekugadzirira kwakanaka kwepamberi. Zvinokurudzirwa kufanogadzirisa iyo data, kuigadzirisa, uye kuipatsanura kuita kudzidziswa uye seti yekuyedza. Uyezve, kusarudza iyo chaiyo network yekuvaka uye yakakwana yekudzidziswa paramita kwakakosha kune yakanyanya mhedzisiro. Neraki, kune akawanda maturusi eAI nemaraibhurari aripo anorerutsa maitiro aya, akadai saTensorFlow, Keras, uye PyTorch.

12. Kufambira mberi kwezvino muArtificial Neural Networks

Kune akawanda akashandura zvakanyanya ndima yehungwaru hwekugadzira. Kufambira mberi uku kwakabvumira kugadzirwa kwemaitiro akanyatsoshanda uye akarurama ekugadzirisa matambudziko akasiyana-siyana munzvimbo dzakadai sekugadzirisa mutauro wechisikigo, kuona kwekombiyuta, uye kuziva maitiro.

Imwe yeanonyanya kufambira mberi ndeyekuitwa kwe convolutional neural network (CNN). Manetiweki aya akave mareferensi akajairwa mumunda wekuona kwekombuta uye aratidza kuita kwakatanhamara mumabasa akadai sekuronga kwemifananidzo uye kuona chinhu. MaCNN anoshandisa convolutional layers kuburitsa akakodzera maficha kubva pamifananidzo yekuisa, inoteverwa neakazara akabatana maseru kuti aite chikamu chekupedzisira. Ichi chivakwa chakaratidza kuve chakanyanya kushanda uye chakapfuura nzira dzakawanda dzechinyakare mukugadzirisa mifananidzo.

Kumwe kufambira mberi kwakakosha kushandisa recurrent neural network (RNN) yekugadzirwa kwemutauro wechisikigo. MaRNN anokwanisa kutevedzera kutevedzana uye kutsamira kwenguva, zvichiita kuti zvive zvakakosha mumabasa akadai sekushandura nemuchina, kuziva kutaura, uye kugadzira zvinyorwa. Imwe mhando ine simba yeRNN ndiyo yekutarisisa modhi, iyo inobvumira network kuti itarise pane dzakati mativi ekuisa panguva yechizvarwa maitiro. Maitiro aya aunza kuvandudzwa kukuru mumhando yeshanduro dzemuchina uye akagonesa kufambira mberi munzvimbo dzakadai sekugadzira otomatiki zvinyorwa zvidiki uye synthesis yekutaura.

13. Hunhu uye kufunga kwekuvanzika mukushandiswa kweArtificial Neural Networks

Hunhu uye kuvanzika kufunga zvinhu zviviri zvakakosha zvekufunga nezvazvo paunenge uchishandisa Artificial Neural Networks (ANN). Aya maturusi ehungwaru ane simba ekugadzira ane mukana wekuita hukuru hwakakura mundima dzakasiyana siyana, kusanganisira hutano, kururamisira, uye bhizinesi. Naizvozvo, zvakakosha kugadzirisa nyaya dzehunhu uye zvakavanzika zvine chekuita nekuitwa kwayo.

Rimwe rematambudziko makuru ehunhu ndere kuvimbisa kujeka uye kutsanangurwa kwesarudzo dzakaitwa nemaANN. Sezvo ari akaomesesa algorithms, zvinodikanwa kuti unzwisise kuti imwe mhedziso inosvika sei. Izvi zvinoreva kuti vanogadzira vanofanirwa kugadzira mamodheru anodudzirwa, kuitira kuti tinzwisise uye tigoona zvawanikwa.

Pamusoro pezvo, kuvanzika kwedata zvakare chinhu chakakosha chekufunga nezvacho. MaANN anowanzoda ruzivo rwakakura kuti adzidzise uye agadzirise maparamita awo. Izvo zvakakosha kuve nechokwadi chekuti data rinoshandiswa rakachengetedzwa, kudzivirira kuburitswa kana kushandiswa zvisizvo kweruzivo rwemunhu kana rwakadzama. Izvi zvinosanganisira kushandisa kusazivikanwa uye nzira dzekunyorera, pamwe nekutora yakasimba mitemo yekuvanzika kuti ive nechokwadi chekuvanzika kwedata.

14. Ramangwana reArtificial Neural Networks mune tekinoroji uye nzanga

Artificial neural network yakaratidza hukuru hukuru munzvimbo dzakasiyana dzetekinoroji uye nzanga. Nekufambiswa mberi kwehungwaru hwekugadzira, network idzi dziri kuita chishandiso chakakosha kugadzirisa matambudziko akaomarara uye kuita mabasa aimbove asingafungidzike. Kugona kwavo kudzidza uye kugadzirisa kunoita kuti vakwanise kugadzirisa yakawanda data uye kuziva mapatani mukati nguva chaiyo.

Mune ramangwana, artificial neural network anotarisirwa kuita basa rakakosha mukuvandudza tekinoroji. Kushandiswa kwaro kuchasvika kuminda yakaita semushonga, marobhoti, indasitiri yemotokari uye chengetedzo, pakati pezvimwe. Semuenzaniso, mune zvekurapa, neural network inogona kushandiswa kuongorora zvirwere zvakanyanya uye nekumhanyisa tsvagiridzo mukurapa kutsva. Muindasitiri yemotokari, maneural network anotarisirwa kuita basa rakakosha mukutyaira akazvimiririra, achibvumira mota kuita sarudzo dzenguva-chaiyo zvichienderana nekuongorora nharaunda yavo.

Saizvozvo, kukanganisa kweartificial neural network munharaunda Zvichava zvakakosha. Munzvimbo yebasa, otomatiki inotungamirwa neaya network inotarisirwa kuve nemhedzisiro yakakura pamabatiro atinoita basa redu. Mamwe mabasa enguva dzose anogona kuitwa nemichina, achisunungura vanhu kuti vaite mamwe mabasa akaoma uye ekugadzira. Nekudaro, zvimhingamipinyi zvine chekuita nehunhu uye kuvanzika zvichamukawo, sezvo kushandiswa kwemanetiweki aya kunosanganisira kubata kwehuwandu hwakakura hwe data remunhu. Naizvozvo, zvichave zvakakodzera kumisa mirau uye vimbiso kuchengetedza kodzero dzevanhu uye kuona kushandiswa zvine musoro kweaya matekinoroji.

Muchidimbu, artificial neural network inzira ine simba yehungwaru hwekugadzira iyo yakashandura minda yakawanda mumakore achangopfuura. Manetiweki aya anofemerwa nekushanda kwehuropi hwemunhu uye ane akawanda akaturikidzana emanodhi akabatana anobvumira kugadziridzwa kweruzivo nenzira inofambirana zvakanyanya. Kuburikidza nekudzidza uye nekugonesa uremu hwetiweki, artificial neural network inogona kudzidza kuziva mapatani akaoma uye kuita sarudzo dzakaringana.

Artificial neural network yaratidza kuti inonyanya kushanda mumabasa akadai sekuziva kutaura, kugadzirisa mifananidzo, kududzira muchina, uye kufanotaura nguva. Kugona kwavo kugadzirisa uye kudzidza kubva kuhuwandu hwe data kunoita kuti ive chishandiso chakakosha chekugadzirisa matambudziko akaomarara anoda hukuru-hukuru hwekuongororwa uye kugadzirisa.

Sezvo tekinoroji ichiramba ichifambira mberi, artificial neural network angangoramba achishanduka nekuvandudza. Tsvagiridzo mundima iyi inotarisa pakuita kuti network ishande, inokurumidza uye yakarurama, izvo zvinozobvumira kushandiswa kwavo munzvimbo dzakasiyana siyana dzemaindasitiri nenzvimbo dzekufunda.

Kunyangwe artificial neural network iri nzira inovimbisa, inopawo zvinonetsa uye zvinogumira. Kudzidzira manetwork aya kunogona kuda kuwanda kwedata uye nguva yekombuta, uye kududzira mhedzisiro dzimwe nguva kunogona kuve kwakaoma nekuda kwekushaikwa kwekubuda pachena kuti sarudzo inoitwa sei.

Pasinei nematambudziko aya, artificial neural network anoramba ari chimwe chezvishandiso zvinonakidza uye zvine simba mumunda wehungwaru hwekugadzira. Kugona kwayo kugadzirisa ruzivo rwakaoma uye kuita mabasa akaomarara kwakatungamira kufambiro mberi kwakakosha mumhando dzakasiyana dzezvirango. Sezvo isu tichiramba tichiwana maapplication matsva nekuvandudza artificial neural network tekinoroji, tine chokwadi chekuona kufambira mberi kunofadza mune ramangwana.