Ukufunda ngoomatshini: I-Artificial Intelligence Revolution

UkuFunda ngoomatshini (ML) yintsimi ye-Artificial Intelligence (AI) ezinikele ekuphuhliseni i-algorithms enokufunda ngokuzenzekelayo kwiidatha ngaphandle kokucwangciswa ngokucacileyo. Yenye yezona ndawo zithembisayo ze-AI kwaye inefuthe elibonakalayo kuluhlu olubanzi lwamashishini, afana nokhathalelo lwempilo, imali, ezothutho kunye nokuthengisa.

Zimbini iindidi eziphambili ze-ML: iSifundo esiLawulayo kunye nesiFundo esingajongwanga. Kwimfundo egadiweyo, i-algorithm inikwe isethi yedatha ebhaliweyo, oko kukuthi, idatha eneempendulo ezichanekileyo. I-algorithm ifunda ukudibanisa amagalelo kunye neziphumo ezichanekileyo. Ekufundeni okungajongwanga, i-algorithm ayinazo iilebhile. Kufuneka ufunde ukufumana iipateni kwidatha ngokwakho.

Ezinye zezona algorithms zidumileyo zokuFunda ngoomatshini zezi:

• Ukuhlehla komgca
• Umthi wesigqibo
• Inethiwekhi yangaphakathi
• Umatshini wokuxhasa iVector

Ezi algorithms zinokusetyenziselwa ukusombulula uluhlu olubanzi lweengxaki, ezinje:

• Ukwahlula
• Uxinzelelo
• Ukuhlela ibhetshi
• ukufunda okunzulu

Esi sisixhobo esinamandla esinamandla okuguqula amashishini amaninzi. Njengoko ii-algorithms zeML zisiba nobugocigoci ngakumbi, sinokulindela ukubona usetyenziso olutsha ngakumbi kwixesha elizayo.

Isebenza njani iMfundo ngoomatshini?

I-ML isebenza ngokusebenzisa idatha ukuqeqesha i-algorithm. I-algorithm ifunda ukudibanisa amagalelo kunye neziphumo ezivela kwidatha. Emva kokuba i-algorithm iqeqeshiwe, ingasetyenziselwa ukwenza uqikelelo kwidatha entsha.

Umzekelo, i-algorithm yokuFunda koMatshini inokuqeqeshwa ukuchonga iikati kwimifanekiso. I-algorithm iya kuqeqeshwa nge-dataset ye-cat kunye ne-non-cat imifanekiso. I-algorithm iya kufunda ukuchonga iimpawu zemifanekiso yekati, njengokumila kwentloko, amehlo kunye nomsila. Nje ukuba i-algorithm iqeqeshwe, ingasetyenziselwa ukuchonga iikati kwimifanekiso emitsha.

Ziziphi iingenelo zokuFunda ngoomatshini?

Iingenelo zininzi. Ezinye zezona zibonelelo zibalulekileyo ziquka:

• Ukuzenzekela: I-ML inokwenza imisebenzi emininzi eyenziwa ngoku ngabantu. Oku kunokukhulula ixesha kunye nezixhobo zokuba abantu bagxile kwimisebenzi enobuchule ngakumbi.

• Ukuchaneka: I-ML inokuchaneka ngakumbi kuneendlela zokuhlalutya zendabuko. Oku kungenxa yokuba i-Machine Learning inokufunda kwidatha kwaye ilungise ukuqikelelwa kwayo ngokusekelwe kwidatha entsha.

• Ukusebenza kakuhle: I-ML inokusebenza ngakumbi kuneendlela zokuhlalutya zendabuko. Oku kungenxa yokuba ukuFunda ngoomatshini kunokuqhuba inani elikhulu ledatha ngokukhawuleza nangokufanelekileyo.

• Ukuqaliswa kokutsha: I-ML inokunceda ukuvelisa iingcamango ezintsha kunye nezinto ezintsha. Oku kungenxa yokuba iMfundo ngoomatshini inokufunda kwidatha kwaye ifumane iipateni ezingenakubonwa ngabantu.

Yeyiphi imingeni yokuFunda koomatshini?

Imingeni yokuFunda koomatshini nayo mininzi. Eminye yeyona mingeni ibalulekileyo ibandakanya:

• Ukufumaneka kwedatha: I-MLearning ifuna amanani amakhulu edatha ukuqeqesha i-algorithms. Kunokuba nzima ukufumana idatha efunekayo, ngakumbi ukuba idatha iyimfihlo okanye i-copyright.

• Ubunzima bedatha: Idatha inokuba nzima kwaye kunzima ukuyihlalutya. Oku kunokwenza kube nzima ukuqeqesha ii-algorithms ze-MLearning ezichanekileyo.

• Ukutolika iziphumo zakho: Iziphumo zakho kunokuba nzima ukuzitolika. Oku kungenxa yokuba i-MLearning algorithms inokufunda iipateni ezingenakubonwa ngabantu.

Ngaphandle kwemiceli mngeni, i-ML yitekhnoloji enamandla amakhulu empembelelo entle kwihlabathi. Njengoko ii-algorithms zokuFunda koMatshini zisiba nobuchule ngakumbi, sinokulindela ukubona usetyenziso oluyilayo ngakumbi kwixesha elizayo.

Ndingafunda njani ngakumbi ngokuFunda koomatshini?

Ukuba ufuna ukufunda ngakumbi malunga noku, kukho izixhobo ezininzi ezikhoyo. Unokufumana iincwadi, amanqaku, iikhosi ze-intanethi kunye nezifundo. Unokufumana uluntu lwabasebenzisi kunye neeforamu apho unokufunda khona kwabanye abanomdla kwiSifundo soomatshini.

Ukuba unomdla wokufunda ngakumbi, sincoma ukuqala ngeziseko. Funda malunga neentlobo ezahlukeneyo zee-algorithms zokuFunda koMatshini, indlela ezisebenza ngayo, kunye nendlela ezinokusetyenziswa ngayo ukusombulula iingxaki. Nje ukuba ube nokuqonda okusisiseko kweziseko, ungaqala ukufunda malunga nezicelo ezithile.

Zeziphi iintlobo ezahlukeneyo zokuFunda ngoomatshini?

Kukho iindidi ezimbini eziphambili zokuFunda ngoomatshini: ukuFunda okuLawulwayo kunye nokuFunda okungagadwanga.

UkuFunda ngokuBekwa

Kwimfundo egadiweyo, i-algorithm inikwe isethi yedatha ebhaliweyo, oko kukuthi, idatha eneempendulo ezichanekileyo. I-algorithm ifunda ukudibanisa amagalelo kunye neziphumo ezichanekileyo.

UkuFunda okungalawulwa

Ekufundeni okungajongwanga, i-algorithm ayinazo iilebhile. Kufuneka ufunde ukufumana iipateni kwidatha ngokwakho. Ngokomzekelo, i-algorithm yokufunda engajongwanga inokuqeqeshwa ukuba ihlanganise abathengi kwiindidi ezahlukeneyo. I-algorithm iya kufunda ukufumana iipateni kwidatha yabathengi, njengeminyaka yabo, umvuzo kunye nendawo. Emva kokuba i-algorithm iqeqeshiwe, ingasetyenziselwa ukuhlanganisa abathengi abatsha kwiindidi ezifanayo.

Zeziphi ezinye zezicelo zokuFunda ngoomatshini?

I-ML isetyenziswa kuluhlu olubanzi lwamashishini, afana nokhathalelo lwempilo, imali, ezothutho, kunye nokuthengisa. Ezinye zezona apps zidumileyo ziquka:

• Ukwahlula: IM. Ukufunda kungasetyenziselwa ukuhlela idatha ngokweendidi ezahlukeneyo. Umzekelo, i-algorithm yokuFunda ngoMatshini ingasetyenziselwa ukwahlula imifanekiso yeekati nezinja.
• Uxinzelelo: M Ukufunda kungasetyenziselwa ukuqikelela ixabiso eliqhubekayo. Ngokomzekelo, i-algorithm yokuFunda ngoMatshini ingasetyenziselwa ukuqikelela ixabiso lesitokhwe okanye amathuba okuba umthengi aqhube.
• Ukwahlulahlula: IM. Ukufunda kunokusetyenziselwa ukuhlanganisa idatha kwiindidi ezahlukeneyo. Umzekelo, i-algorithm yokuFunda ngoomatshini inokusetyenziselwa ukuqokelela abathengi ngokweendidi ezahlukeneyo ngokusekelwe kwiimpawu zabo.
• ukufunda okunzulu: Ukufunda ngoomatshini kungasetyenziselwa ukwakha iimodeli ezikwaziyo ukufunda kwiimali ezinkulu zedatha. Ngokomzekelo, i-algorithm yokufunda enzulu ingasetyenziselwa ukuchonga imifanekiso yomhlaza webele kwiimammograms.

Zeziphi ezinye zeentsingiselo ze-MLearning zexesha elizayo?

Ezinye zeendlela zokuFunda ngoomatshini kwixesha elizayo ziquka:

• Ukwanda kokusetyenziswa kwedatha enkulu: Izixa ezikhulu zedatha ziyafuneka ukuqeqesha i-algorithms. Njengoko ihlabathi lisiba yidijithali ngakumbi, idatha eninzi yenziwa. Oku kudala amathuba amatsha okusetyenziswa kwayo.

• Ukuphuhliswa kwe-algorithms entsha: Abaphandi bahlala bephuhlisa ii-algorithms zokuFunda koMatshini. Ezi algorithms zintsha zichanekile kwaye zisebenza kakuhle kunee-algorithms zangaphambili.

• Su sebenzisa kwiindawo ezintsha: Ukufunda ngoomatshini kusetyenziswa kuluhlu olubanzi lweenkalo, ezifana nokhathalelo lwempilo, imali, uthutho, kunye nokuthengisa. Njengoko itekhnoloji isiya iphucuka ngakumbi, sinokulindela ukubona ukusetyenziswa kwayo kwiinkalo ezintsha.

I-MLearning bubuchwepheshe obunamandla obunamandla okuguqula amashishini amaninzi. Njengoko ezi algorithms zisiba nobuchule ngakumbi, sinokulindela ukubona usetyenziso olutsha ngakumbi kwixesha elizayo.