I-Machine Learning (ML) inkambu ye-Artificial Intelligence (AI) enikelwe ekwakheni ama-algorithms angafunda ngokuzenzakalela kudatha ngaphandle kokuhlelwa ngokusobala. Ingenye yezindawo ezithembisa kakhulu ze-AI futhi inomthelela omkhulu ezimbonini eziningi ezihlukene, ezihlanganisa ezempilo, ezezimali, ezokuthutha, nezokudayisa.
Kunezinhlobo ezimbili eziyinhloko ze-ML: Ukufunda Okugadiwe kanye nokufunda okungagadiwe. Ekufundeni okugadiwe, i-algorithm inikezwa isethi yedatha enelebula, okungukuthi, idatha enezimpendulo ezifanele. I-algorithm ifunda ukuhlobanisa okokufaka nokuphumayo okulungile. Ekufundeni okungagadiwe, i-algorithm ayinawo amalebula. Kufanele ufunde ukuthola amaphethini kudatha ngokwakho.
Amanye ama-algorithms aziwa kakhulu wokufunda ngomshini yilawa:
- Ukwehla komugqa
- Isihlahla sesinqumo
- Inethiwekhi yeNeural
- umshini wokusekela i-vector
Lawa ma-algorithms angasetshenziswa ukuxazulula izinkinga eziningi, njenge:
- Ukuhlukaniswa
- Ukuhlehliswa
- ukuhlunga iqoqo
- ukufunda okujulile
Leli ithuluzi elinamandla elinamandla okuguqula izimboni eziningi. Njengoba ama-algorithms e-ML eba yinkimbinkimbi kakhulu, singalindela ukubona izinhlelo zokusebenza ezintsha kakhulu esikhathini esizayo.
Kusebenza kanjani ukufunda ngomshini?
I-ML isebenza ngokusebenzisa idatha ukuqeqesha i-algorithm. I-algorithm ifunda ukuhlobanisa okokufaka nokuphuma kudatha. Uma i-algorithm isiqeqeshiwe, ingasetshenziswa ukwenza izibikezelo kudatha entsha.
Isibonelo, i-algorithm yokufunda ngomshini ingaqeqeshelwa ukukhomba amakati ezithombeni. I-algorithm izoqeqeshwa kudathasethi yezithombe zekati nezingezona zekati. I-algorithm izofunda ukukhomba izici zezithombe zekati, njengokuma kwekhanda, amehlo, nomsila. Uma i-algorithm isiqeqeshiwe, ingasetshenziswa ukukhomba amakati ezithombeni ezintsha.
Yiziphi izinzuzo zokufunda ngomshini?
Izinzuzo ziningi. Ezinye zezinzuzo ezibaluleke kakhulu zihlanganisa:
- Ukuzenzakalela: I-ML ingakwazi ukuzenzela imisebenzi eminingi eyenziwa abantu okwamanje. Lokhu kungakhulula isikhathi nezinsiza ukuze abantu bagxile emisebenzini enamasu amaningi.
- Ukunemba: I-ML ingaba nembe kakhulu kunezindlela ezijwayelekile zokuhlaziya. Lokhu kungenxa yokuthi ukufunda komshini kungafunda kudatha futhi kulungise ukuqagela kwayo ngokusekelwe kudatha entsha.
- Ukusebenza kahle: I-ML ingasebenza kahle kunezindlela zokuhlaziya ezijwayelekile. Lokhu kungenxa yokuthi Ukufunda Ngomshini kungacubungula amanani amakhulu edatha ngokushesha nangempumelelo.
- Ukuqamba okusha: I-ML ingasiza ukuvusa imibono emisha nezinto ezintsha. Lokhu kungenxa yokuthi ukufunda komshini kungafunda kudatha futhi kuthole amaphethini abantu abangakwazi ukuwabona.
Yiziphi izinselelo Zokufunda Ngomshini?
Izinselelo Zokufunda Ngomshini nazo ziningi. Ezinye zezinselelo ezibaluleke kakhulu zihlanganisa:
- Ukutholakala kwedatha: I-MLearning idinga inani elikhulu ledatha ukuqeqesha ama-algorithms. Kungaba nzima ukuthola idatha edingekayo, ikakhulukazi uma idatha iyimfihlo noma ivikelwe yi-copyright.
- Ubunkimbinkimbi bedatha: Idatha ingaba yinkimbinkimbi futhi kube nzima ukuyihlaziya. Lokhu kungenza kube nzima ukuqeqesha ama-algorithms e-MLearning anembile.
- Ukuhunyushwa kwemiphumela: Imiphumela yakho ingaba nzima ukuyitolika. Lokhu kungenxa yokuthi i-MLearning algorithms ingafunda amaphethini abantu abangakwazi ukuwabona.
Naphezu kwezinselelo, i-ML ubuchwepheshe obunamandla amakhulu okuba nomthelela omuhle emhlabeni. Njengoba ama-algorithms wokufunda ngomshini eba yinkimbinkimbi kakhulu, singalindela ukubona izinhlelo zokusebenza ezintsha kakhulu esikhathini esizayo.
Ngingafunda kanjani okwengeziwe mayelana Nokufunda Ngomshini?
Uma ufuna ukufunda okwengeziwe ngalokhu, kunezinsiza eziningi ezitholakalayo. Ungathola izincwadi, izindatshana, izifundo eziku-inthanethi kanye nezifundo. Ungathola futhi imiphakathi yabasebenzisi nezinkundla lapho ungafunda khona kwabanye abathanda ukufunda ngomshini.
Uma ungathanda ukufunda okwengeziwe, sincoma ukuthi uqale ngezisekelo. Funda mayelana nezinhlobo ezahlukene zama-algorithms Wokufunda Ngomshini, ukuthi asebenza kanjani, nokuthi angasetshenziswa kanjani ukuxazulula izinkinga. Uma usunokuqonda okuyisisekelo kwezinto eziyisisekelo, ungaqala ukufunda mayelana nezinhlelo zokusebenza eziqondile.
Yiziphi izinhlobo ezahlukene zokufunda ngomshini?
Kunezinhlobo ezimbili eziyinhloko Zokufunda Ngomshini: Ukufunda Okugadiwe kanye nokufunda okungagadiwe.
Ukufunda Okugadiwe
Ekufundeni okugadiwe, i-algorithm inikezwa isethi yedatha enelebula, okungukuthi, idatha enezimpendulo ezifanele. I-algorithm ifunda ukuhlobanisa okokufaka nokuphumayo okulungile.
Ukufunda okungagadiwe
Ekufundeni okungagadiwe, i-algorithm ayinawo amalebula. Kufanele ufunde ukuthola amaphethini kudatha ngokwakho. Isibonelo, i-algorithm yokufunda engagadiwe ingaqeqeshelwa ukuqoqa amakhasimende ngezigaba ezahlukahlukene. I-algorithm izofunda ukuthola amaphethini kudatha yekhasimende, efana neminyaka yawo, imali engenayo, nendawo. Uma i-algorithm isiqeqeshiwe, ingasetshenziswa ukuhlanganisa amakhasimende amasha ngezigaba ezifanayo.
Yiziphi ezinye zezinhlelo zokusebenza zokufunda ngomshini?
I-ML isetshenziswa ezinhlobonhlobo zezimboni, ezihlanganisa ezokunakekelwa kwempilo, ezezimali, ezokuthutha, nezokudayisa. Ezinye zezinhlelo zokusebenza ezidume kakhulu zifaka:
- Ukuhlukaniswa: Ukufunda kwe-M kungasetshenziswa ukuhlukanisa idatha ngezigaba ezahlukene. Isibonelo, i-algorithm Yokufunda Ngomshini ingase isetshenziselwe ukuhlukanisa izithombe zamakati nezinja.
- Ukuhlehliswa: Ukufunda kwe-M kungasetshenziswa ukubikezela amanani aqhubekayo. Isibonelo, i-algorithm Yokufunda Ngomshini ingase isetshenziselwe ukubikezela intengo yesitoko noma amathuba okuthi ikhasimende lizoyeka ukuba yikhasimende.
- Ukuhlanganisa: Ukufunda kwe-M kungasetshenziswa ukuqoqa idatha ngezigaba ezahlukene. Isibonelo, i-algorithm Yokufunda Ngomshini ingase isetshenziselwe ukuqoqa amakhasimende ngezigaba ezihlukene ngokusekelwe kuzici zawo.
- ukufunda okujulile: Ukufunda Ngomshini kungasetshenziswa ukwakha amamodeli akwazi ukufunda enanini elikhulu ledatha. Isibonelo, i-algorithm yokufunda ejulile ingasetshenziswa ukukhomba izithombe zomdlavuza webele kuma-mammogram.
Yimaphi amanye amathrendi e-MLearning esikhathi esizayo?
Amanye amathrendi Wokufunda Ngomshini wesikhathi esizayo afaka:
- Ukusetshenziswa okukhulayo kwedatha enkulu: Inani elikhulu ledatha liyadingeka ukuqeqesha ama-algorithms. Njengoba umhlaba uba ngedijithali, idatha eyengeziwe iyakhiqizwa. Lokhu kudala amathuba amasha okusetshenziswa kwayo.
- Ukwakhiwa kwama-algorithms amasha: abacwaningi bahlala bethuthukisa ama-algorithms amasha wokufunda ngomshini. Lawa ma-algorithms amasha anembe kakhulu futhi asebenza kahle kunama-algorithms adlule.
- Su sebenzisa emikhakheni emisha: Ukufunda Ngomshini kusetshenziswa emikhakheni eyahlukene, okuhlanganisa ezempilo, ezezimali, ezokuthutha, nokudayisa. Njengoba ubuchwepheshe buba yinkimbinkimbi, singalindela ukubona ukusetshenziswa kwabo emikhakheni emisha.
I-MLearning ubuchwepheshe obunamandla obunamandla okuguqula izimboni eziningi. Njengoba lawa ma-algorithms eba yinkimbinkimbi kakhulu, singalindela ukubona izinhlelo zokusebenza ezintsha kakhulu esikhathini esizayo.