Indlela yokwenza i-algorithm kusukela ekuqaleni: Konke odinga ukukwazi

Informatec Digital » Ama-algorithms » Indlela yokwenza i-algorithm kusukela ekuqaleni: Konke odinga ukukwazi

Ama-algorithms a-odiwe ukulandelana kwemiyalo yokuxazulula izinkinga ezithile kubuchwepheshe.
I-algorithm esebenzayo kufanele ibe nenembile, iphele, isebenze kahle, futhi ijwayeleke kumasethi edatha ahlukene.
Kunezinhlobo ezahlukahlukene zama-algorithms, njengokusesha, ukuhlunga, nokufunda ngomshini, ngezinhlelo zokusebenza zomhlaba wangempela eziningi.
Ukuhlaziya nokwenza ngcono nokuba yinkimbinkimbi kubalulekile ekuthuthukiseni ukusebenza kwama-algorithms asetshenzisiwe.

Ezweni lanamuhla ledijithali, ama-algorithms ayisisekelo sazo zonke izixazululo zobuchwepheshe esizisebenzisa nsuku zonke. Kusukela ekusesheni kwe-Google kuya ezincomweni ze-Netflix, ama-algorithms asebenza ngokuzikhandla ukucubungula idatha nokwenza izinqumo. Kodwa iyini ngempela i-algorithm, futhi uyidala kanjani kusukela ekuqaleni? Kulesi sihloko, ngizokuqondisa ngenqubo ethakazelisayo yokudala i-algorithm, ngikunikeze amathuluzi nolwazi oludingekayo ukuze ube yingcweti yaleli khono eliyisisekelo kwisayensi yamakhompyutha kanye nokuhlela.

Indlela yokwenza i-algorithm kusukela ekuqaleni: Konke odinga ukukwazi

Incazelo ye-algorithm

Ama-algorithms awayona nje ingxenye ebalulekile yokuthuthukiswa kwesofthiwe, kodwa futhi abalulekile emikhakheni efana nobuhlakani bokwenziwa, ukuhlaziya idatha, kanye nokwenza ngcono inqubo. Ukwenza ubuciko bokudala ama-algorithms kuzokuvumela ukuthi uxazulule izinkinga eziyinkimbinkimbi ngempumelelo, uthuthukise amakhono akho okucabanga anengqondo, futhi ugqame emhlabeni wokuncintisana wobuchwepheshe.

Kuso sonke lesi sihloko, sizohlola imiqondo eyisisekelo, imikhuba emihle, namasu athuthukile okuklama ama-algorithm asebenzayo. Noma ngabe ungumuntu osaqala ukwazi noma ungumfundi onolwazi ofuna ukucija amakhono akho, lo mhlahlandlela obanzi uzokunikeza ulwazi oludingayo ukuze udale ama-algorithms aqinile, asebenza kahle kusukela ekuqaleni.

Ngamafuphi, incazelo ye-algorithm ilandelayo: I-algorithm iyisethi yezinyathelo noma imiyalelo ehlelekile nelinganiselwe echaza indlela yokuxazulula inkinga noma ukwenza umsebenzi othize. Iyisisekelo ekubaleni nasekuhleleni ngoba inikeza ukulandelana okunengqondo nokuningiliziwe kwemisebenzi okumele kwenziwe ukuze kufezwe umphumela oyifunayo. Ama-algorithm ayisisekelo lapho izinhlelo zekhompyutha nezinhlelo ezizenzakalelayo zakhiwe khona ukuze kuxazululwe izinkinga ngempumelelo nangendlela ehlelekile.

Indlela Yokwenza I-Algorithm: Okuyisisekelo kanye Nemiqondo Eyisisekelo

Ngaphambi kokuthi singene ohlelweni lokudala ama-algorithms, kubalulekile ukuqonda ukuthi iyini ngempela i-algorithm nokuthi ziyini izici zayo ezibalulekile.

Incazelo nezici ze-algorithm esebenza kahle

I-algorithm, empeleni, isethi yesinyathelo ngesinyathelo imiyalelo eklanyelwe ukuxazulula inkinga ethile noma ukwenza umsebenzi othile. Kodwa akukhona noma yikuphi ukulandelana kwezinyathelo okungabhekwa njenge-algorithm ephumelelayo. Ukuze i-algorithm isebenze ngempela, kufanele ihlangabezane nezici ezithile ezibalulekile:

ngokunemba:Isinyathelo ngasinye se-algorithm kumele sichazwe ngokucacile futhi singadideki.
Isiphetho: I-algorithm kufanele inqamule ngemva kwenani elilinganiselwe lezinyathelo.
Okokufaka okuchaziwe kanye nokuphumayo: Kumelwe ibe nokokufaka okucaciswe ngokucacile futhi ikhiqize imiphumela elindelekile.
Ukusebenza kahle: Kufanele uxazulule inkinga ngesikhathi esifanele nangokusebenzisa izinsiza ngendlela efanele.
Okujwayelekile: Kufanele ikwazi ukuphatha amasethi edatha yokufaka ahlukene ngaphakathi kwesizinda sayo.

Isibonelo esilula se-algorithm kungaba inqubo yokwenza inkomishi yekhofi:

Gcwalisa umenzi wekhofi ngamanzi.
Faka isihlungi kusibambi sokuhlunga.
Engeza ikhofi eligayiwe kusihlungi.
Vula umenzi wekhofi.
Linda kuze kube yilapho ikhofi selilungile.
Phaka ikhofi enkomishini.

Lesi sibonelo, nakuba silula, sibonisa indlela i-algorithm ehlukanisa ngayo umsebenzi ube izinyathelo ezicacile, ezisebenzisekayo.

Izinhlobo zama-algorithms kanye nokusebenza kwawo emhlabeni wangempela

Ama-algorithms angahlukaniswa ngezindlela ezahlukahlukene, kuye ngesakhiwo sawo, inhloso, noma indlela yokuqalisa. Ezinye izinhlobo ezijwayelekile zama-algorithms zifaka:

sesha ama-algorithms: Isetshenziselwa ukuthola into ethile kusethi yedatha. Izibonelo zifaka phakathi ukusesha kanambambili kanye ukusesha komugqa.
Ihlunga ama-algorithms: Idizayinelwe ukuhlela idatha ngendlela ethile. Ama-algorithm adumile afaka i-quicksort ne-mergesort.
Ama-algorithms wegrafu: Isetshenziselwa ukuxazulula izinkinga ezihlobene nezakhiwo zedatha yegrafu, njengokuthola indlela emfushane phakathi kwamaphoyinti amabili.
Ama-algorithms wokufunda komshini: Isetshenziswa kubuhlakani bokwenziwa ukuvumela imishini ukuthi ifunde kudatha futhi ithuthukise ukusebenza kwayo ngokuhamba kwesikhathi.
Ama-algorithms wokucindezela: Idizayinelwe ukunciphisa usayizi wedatha ukuze igcinwe kahle noma idluliselwe.

Indlela Yokusesha Ye-Hash: Umhlahlandlela Ophelele

Emhlabeni wangempela, ama-algorithms anezinhlelo zokusebenza ezingenamkhawulo. Ngokwesibonelo:

Izinjini zokusesha zisebenzisa ama-algorithms ayinkimbinkimbi ukulinganisa kanye nokwethula imiphumela efanele.
Amanethiwekhi ezokuxhumana asebenzisa ama-algorithms ukwenza kube ngokwakho okuqukethwe okubona kokuphakelayo kwakho.
Amasistimu wokuzulazula we-GPS asebenzisa ama-algorithms ukubala umzila osebenza kahle kakhulu phakathi kwamaphoyinti amabili.
Izinhlelo zokuncoma ekusakazeni noma ezinkundleni zokuxhumana ze-e-commerce zisebenzisa ama-algorithms ukuphakamisa imikhiqizo noma okuqukethwe ngokusekelwe kokuncamelayo.

Ukuqonda le miqondo eyisisekelo kubalulekile ukuze uqale ukudala ama-algorithms akho. Esigabeni esilandelayo, sizodlula inqubo yesinyathelo ngesinyathelo yokuklama i-algorithm kusukela ekuqaleni.

Izinyathelo zokudala i-algorithm kusukela ekuqaleni

Indlela yokudala i-algorithm ngumbuzo ovamile phakathi kososayensi bekhompyutha nabafundi. Ukudala i-algorithm ephumelelayo kudinga indlela ehlelekile nehlelekile. Ngokulandela lezi zinyathelo, uzokwazi ukuthuthukisa izixazululo ezinengqondo nezisebenzayo kuhlu olubanzi lwezinkinga.

Ukuhlonza inkinga kanye nencazelo yezinjongo

Isinyathelo sokuqala esibalulekile ekudaleni noma iyiphi i-algorithm ukuqonda ngokucacile inkinga ozama ukuyixazulula. Le nqubo ibandakanya:

chaza inkinga: Ichaza inselele ethile noma umsebenzi okufanele i-algorithm ibhekane nayo. Isibonelo, "Hlunga uhlu lwezinombolo kusukela kwencane kakhulu kuye kwenkulu."
Ukusungula izinjongo: Thola ukuthi iyiphi i-algorithm okufanele izuzwe. Esibonelweni sethu, umgomo uzoba "Khiqiza uhlu olu-odwe lwezinombolo ngendlela ekhuphukayo."
Thola izingqinamba: Cabangela noma imiphi imikhawulo noma izimfuneko ezikhethekile. Lokhu kungase kuhlanganise imikhawulo yesikhathi sokusebenza, ukusetshenziswa kwememori, noma izinhlobo ezithile zedatha.
Nquma ububanzi: Chaza ngokucacile ukuthi yiziphi izici zenkinga i-algorithm yakho ezobhekana nazo nokuthi yiziphi ezizoba ngaphezu kobubanzi bayo.

Uma usuyichaze ngokucacile inkinga nezinjongo zakho, uzoba sesimweni esingcono sokuklama isixazululo esisebenzayo.

Ukuhlaziywa kwedatha yokufaka kanye nokuphumayo okulindelekile

Isinyathelo esilandelayo siwukuqonda kahle idatha yakho ye-algorithm ezosebenza ngayo:

Khomba idatha yokufaka: Yiluphi ulwazi oluzotholwa yi-algorithm yakho? Esibonelweni sethu sokuhlunga, kuzoba uhlu lwezinombolo olungahlelekile.
Nquma ifomethi yokufaka: Le datha izokwethulwa kanjani? Ingabe azoba uhlu, uhlu, ifayela lombhalo?
Chaza okukhiphayo okulindelekile: Yini okufanele i-algorithm yakho ikhiqize? Esimweni sethu, kungaba uhlu olu-odwe lwezinombolo.
Cabangela izimo ezikhethekile: Cabanga ngezimo ezeqisayo noma ezingajwayelekile. Kufanele wenzeni i-algorithm yakho uma uhlu lungenalutho noma uma zonke izinombolo zilingana?

Lokhu kuhlaziya kuzokusiza ukuthi udizayine i-algorithm engaphatha ngempumelelo zonke izimo ezingaba khona.

Idizayini ye-logic kanye nesakhiwo se-algorithm

Ngokuqonda okucacile kwenkinga nedatha, ungaqala ukudizayina i-algorithm ye-algorithm yakho:

Hlukanisa inkinga ibe yizinkinga ezincane: Hlukanisa inkinga enkulu ibe yizinyathelo ezincane, ezilawulekayo.
Yakha isu jikelele: Nquma ukuthi iyiphi indlela ozoyisebenzisa ukuxazulula inkinga. Ngesibonelo sethu sokuhlunga, ungakhetha indlela efana nokuhlunga ibhamuza noma ukuhlunga okusheshayo.
Chaza izinyathelo ezibalulekile: Dala uhlaka lwezinga eliphezulu lwezinyathelo ezizolandelwa i-algorithm yakho.
Cwenga isinyathelo ngasinye: Thuthukisa imininingwane yesinyathelo ngasinye, ucabangela indlela yokusingatha izimo ezihlukene kanye namacala asemaphethelweni.
Cabangela ukusebenza kahle: Cabanga ngendlela ongayilungiselela ngayo i-algorithm yakho ukuthi isebenze kahle ngangokunokwenzeka ngokuya kwesikhathi nokusetshenziswa kwensiza.

Isibonelo, uhlaka lokuqala lwe-algorithm yethu yokuhlunga kungaba:

Thola uhlu olunga-odwe.
Qhathanisa izakhi ezincikene.
Shintshanisa izinto uma zilandelana ngendlela engafanele.
Phinda inqubo kuze kungabe kusadingeka ukushintshana.
Buyisa uhlu oluhlungiwe.

Lo mklamo wokuqala unikeza isisekelo esiqinile sokuthuthukisa i-algorithm enemininingwane eminingi futhi ecwengisisiwe. Masiqhubeke nokuthola indlela yokwenza i-algorithm.

Amathuluzi namasu okudala ama-algorithms

Ukuze uguqule umklamo wakho womqondo ube yi-algorithm yokusebenza, kunamathuluzi namasu amaningana ongawasebenzisa. Lokhu kuzokusiza ukuthi ubone ngeso lengqondo, uhlele, futhi uxhumane ne-algorithm yakho ngempumelelo.

I-pseudocode nama-flowcharts: Ukubaluleka kwawo ekwakhiweni

I-pseudocode kanye nama-flowchart angamathuluzi ayigugu enqubweni yokuklama i-algorithm, njengoba akuvumela ukuthi umelele ingqondo yesisombululo sakho ngendlela ecacile nehlelekile ngaphambi kokutshuza ekubhaleni amakhodi kwangempela.

I-Genetic Algorithms: Umqondo kanye Nezicelo

Ikhodi Engamanga : Ikhodi Engamanga iyincazelo esezingeni eliphezulu, engakahleleki ye-algorithm esebenzisa ingxube yolimi lwemvelo kanye nezakhiwo zokuhlela ezilula. Iwusizo kakhulu ngoba:

Kwenza kube lula ukuhlela nokuhlela imibono yakho.
Kulula ukufunda nokuqonda kunekhodi yangempela.
Ikuvumela ukuthi ugxile ku-logic ngaphandle kokukhathazeka mayelana ne-syntax ethize ye-a ulimi lohlelo.

Isibonelo se-pseudocode se-algorithm yethu yokuhlunga:

FUNCIÓN ordenar(lista):

n = longitud de lista

PARA i DESDE 0 HASTA n-1:

PARA j DESDE 0 HASTA n-i-1:

SI lista > lista:

intercambiar lista y lista

DEVOLVER lista

Ama-Flowchart : Ama-Flowchart ayizithombe ezibonisa ukugeleza kokulawula ku-algorithm. Awusizo ngoba:

Banikeza umbono ocacile wenqubo.
Basiza ukukhomba izihibe, izimo kanye nezinqumo.
Benza lula ukuxhumana komqondo we-algorithm kwabanye.

I-flowchart elula ye-algorithm yethu yokuhlunga ingase ibukeke kanje:

 →  →  → (Sí) →  →

↓ (No)
↓

 → (Sí) →

↓ (No)

↓

Izilimi zokuhlela zilungele ukusebenzisa ama-algorithms

Uma usudizayine i-algorithm yakho usebenzisa i-pseudocode nama-flowchart, isinyathelo esilandelayo ukuwenza ngolimi lwangempela lokuhlela. Ukukhethwa kolimi kuzoncika ezintweni ezimbalwa, okuhlanganisa:

Ubunjalo benkinga: Ezinye izilimi zifaneleka kangcono izinhlobo ezithile zama-algorithms noma izinhlelo zokusebenza.
Ukusebenza kahle okudingekayo: Izilimi ezithile zinikeza ukusebenza okungcono kwemisebenzi ethile.
Ukujwayela kanye nolwazi: Kulula ukusebenzisa ama-algorithms ngezilimi ozazi kahle.
Izinsiza ezitholakalayo: Cabangela imitapo yolwazi namathuluzi atholakala ngolimi ngalunye.

Ezinye izilimi ezidumile zokusebenzisa ama-algorithms zifaka:

Python: Ilungele ukwenza i-prototyping ngokushesha futhi kulula ukuyifunda. Inezinhlobonhlobo zemitapo yolwazi yama-algorithms nezakhiwo zedatha.
C ++: Inikeza ukusebenza okuphezulu nokulawulwa kwezinga eliphansi, ilungele ama-algorithms adinga ukusebenza kahle okuphezulu.
Java: Ihlinzeka ngokulingana okuhle phakathi kokusebenza nokusebenziseka kalula, ngomphakathi omkhulu nezinsiza.
i-JavaScript: Iwusizo kuma-algorithms azosebenza kuziphequluli zewebhu noma ezindaweni ze-Node.js.
R: Ikhethekile kuma-algorithms ezibalo nokuhlaziywa kwedatha.

Isibonelo, i-algorithm yethu yokuhlunga esetshenziswe ku-Python ingase ibukeke kanje:

i-python

def ordenar(lista):

n = len(lista)

for i in range(n):

for j in range(0, n - i - 1):

if lista > lista:

intercambiar lista y lista

return lista

Khumbula ukuthi ukukhetha kwakho ulimi kufanele kuncike ezidingweni ezithile zephrojekthi yakho kanye namakhono akho kanye nezinto ozikhethayo.

Ukwenza ngcono nokuthuthukiswa kwama-algorithms

Sesivele siyayazi indlela yokwenza i-algorithm. Uma ususebenzise i-algorithm yakho, isinyathelo esilandelayo esibalulekile wukuyenza ibe ngcono ukuze ithuthukise ukusebenza kahle kwayo nokusebenza kwayo. Ukwenziwa ngcono kwe-algorithm kuyinqubo eqhubekayo engenza umehluko phakathi kwesixazululo esisebenzayo nesihamba phambili.

Ubunkimbinkimbi be-algorithmic nokuhlaziya ukusebenza kahle

Ukuhlaziywa kobunzima kuyithuluzi eliyisisekelo lokuhlola nokwenza ngcono ukusebenza kahle kwe-algorithm. Igxila ekutheni isikhathi sokwenziwa kwe-algorithm kanye nokusetshenziswa kwenkumbulo kukhula kanjani njengoba usayizi wedatha yokufaka ukhula. Izinhlobo ezimbili eziyinhloko zobunkimbinkimbi ezihlaziywayo yilezi:

Isikhathi esiyinkimbinkimbi: Ikala ukuthi i-algorithm ithatha isikhathi esingakanani ukusebenza ngokusekelwe kusayizi wokufakwayo.
Ubunkimbinkimbi bendawo: Ihlola ukuthi ingakanani inkumbulo esetshenziswa yi-algorithm phakathi nokusebenza kwayo.

I-Big O notation iyindlela ejwayelekile kakhulu yokuveza ubunkimbinkimbi be-algorithmic. Ngokwesibonelo:

O(1): Isikhathi esivamile (esifanele)
O(log n): Isikhathi se-Logarithmic (sisebenza kahle kakhulu)
O(n): Isikhathi somugqa (esisebenzayo)
O(n log n): Isikhathi somugqa we-Logarithmic (sisebenza kahle kakhulu)
O(n²): Isikhathi sequadratic (singase sibe inkinga kumasethi amakhulu edatha)
O(2^n): Isikhathi esichazayo (ngokuvamile asisebenzi ezinkingeni ezinkulu)

Ngesibonelo sethu se-algorithm yokuhlunga ibhamuza, isikhathi esiyinkimbinkimbi sithi O(n²) esimweni esibi kakhulu, okusho ukuthi asisebenzi kahle ezinhlwini ezinkulu.

Ukuze uthuthukise ukusebenza kahle, ungase ucabange ukusebenzisa i-algorithm yokuhlunga esebenza kahle kakhulu efana ne-quicksort, enobunzima obuyisilinganiso buka-O(n log n):

i-python

def quicksort(arr):

if len(arr) <= 1:

return arr

pivot = arr

left = 

middle = 

right = 

return quicksort(left) + middle + quicksort(right)

Le algorithm isebenza kahle kakhulu ezinhlwini ezinkulu.

I-algorithm yokulungisa iphutha kanye namasu okuhlola

Ukulungisa iphutha nokuhlola kubalulekile ukuze uqinisekise ukuthi i-algorithm yakho isebenza ngendlela efanele nangempumelelo. Amanye amasu awusizo ahlanganisa:

Ukuhlolwa kweyunithi: Bhala izivivinyo zengxenye ngayinye ye-algorithm yakho.
Amacala Okuhlolwa Kwemingcele: Hlola i-algorithm yakho ngamakesi asemaphethelweni (uhlu olungenalutho, uhlu lwento eyodwa, njll.).
Ukuhlolwa kokusebenza: Ilinganisa isikhathi sokwenza nokusetshenziswa kwenkumbulo kumasayizi okufaka ahlukene.
Ukulungisa iphutha ngesinyathelo: Sebenzisa i-debugger ukuze ulandele ukusetshenziswa kwe-algorithm yakho umugqa ngomugqa.

Isibonelo sokuhlolwa kweyunithi ye-algorithm yethu yokuhlunga:

i-python

import unittest

class I-TestQuicksort(unittest.I-TestCase):
def test_sort_empty_list(uqobo):
uqobo.qinisekisaEqual(usuthu(), )

def test_sort_list_one_element(uqobo):
uqobo.qinisekisaEqual(usuthu(), )

def test_sort_unordered_list(uqobo):
uqobo.qinisekisaEqual(usuthu(),

if __i-yam__ == '__okuyinhloko__':
unittest.main()

Lezi zivivinyo zisiza ukuqinisekisa ukuthi i-algorithm yakho isebenza kahle ezimeni ezahlukene.

I-athikili ehlobene:

I-Quantitative Algorithm: Izihluthulelo Eziyisi-7 Zokuba Ingcweti Ukuhweba Okuzenzakalelayo

Indlela yokwenza i-algorithm

Indlela yokwenza i-algorithm: Isicelo Esisebenzayo

Manje njengoba sesihlanganise izinto eziyisisekelo namasu athuthukile, ake sibone ukuthi singakusebenzisa kanjani konke lokhu esibonelweni esisebenzayo. Ake sithi sifuna ukwakha i-algorithm ukuze sithole inombolo evame kakhulu ohlwini.

i-python

from collections import Counter

def inombolo_evame kakhulu(uhlu):
if hhayi uhlu:
ukubuya None
counter = Counter(uhlu)
ukubuya counter.okuvamile_kakhulu(1)

# Isibonelo sokusetshenziswa
izinombolo =
ukuphrinta("Inombolo evame kakhulu ithi:", inombolo_evame kakhulu(izinombolo))

Le algorithm isebenzisa isigaba Counter I-Python ukubala ukuvela kwenombolo ngayinye bese ibuyisela evame kakhulu. Isikhathi sayo siyinkimbinkimbi ngu-O(n), lapho u-n eyinombolo yezinto ezisohlwini, okwenza lusebenze kahle kakhulu.

I-FAQ: Uyenza kanjani i-algorithm

Uyini umehluko phakathi kwe-algorithm nohlelo lwekhompyutha?

I-algorithm iyisethi yezinyathelo ezinengqondo zokuxazulula inkinga, kuyilapho uhlelo lwekhompyutha luwukusebenzisa i-algorithms eyodwa noma ngaphezulu ngolimi oluthile lokuhlela. Ama-algorithms azimele ngolimi, kuyilapho izinhlelo ziboshelwe olimini oluthile.

Ngingawathuthukisa kanjani amakhono ami okudala i-algorithm?

Zijwayeze njalo ukuxazulula izinkinga ze-algorithmic, ubambe iqhaza ezinseleleni zokubhala amakhodi ku-inthanethi, izakhiwo zedatha yocwaningo nama-algorithms akudala, futhi uhlaziye izixazululo zabanye abahleli. Ukuzijwayeza njalo kanye nokuchayeka ezinkingeni ezahlukahlukene kuyisihluthulelo sokuthuthukisa.

Imaphi amathuluzi engingawasebenzisa ukuze ngibone ngeso lengqondo ama-algorithms ami?

Kunamathuluzi amaningana awusizo afana ne-draw.io yokudala ama-flowchart, i-PythonTutor yokubuka ukukhishwa kwekhodi isinyathelo ngesinyathelo, namathuluzi okwenza iphrofayela kuma-IDE afana ne-PyCharm noma Ikhodi ye-Visual Studio ukuze uhlaziye ukusebenza.

Ngingayikhetha kanjani i-algorithm engcono kakhulu yenkinga ethile?

Cabangela izici ezifana nobunkimbinkimbi besikhathi nesikhala, imvelo yedatha yokufaka, izidingo zokusebenza, kanye nokusebenziseka kalula nokunakekelwa. Kuyasiza kakhulu ukusebenzisa nokuqhathanisa izixazululo eziningi ukuze uthole esilungile.

Ingabe ama-algorithms ahlala eqinisekisa isixazululo esingcono kakhulu?

Hhayi njalo. Ezinye izinkinga ziyinkimbinkimbi kangangokuthi ukuthola isixazululo esilungile kungase kungenzeki ngekhompyutha. Kulezi zimo, i-approximation noma i-heuristic algorithms isetshenziswa enikeza izixazululo "ezinhle ngokwanele" ngesikhathi esifanele.

Ngingawaphatha kanjani amasethi amakhulu edatha kuma-algorithms ami?

Kumasethi amakhulu edatha, cabangela amasu afana nokucubungula inqwaba, ukufana, ukusetshenziswa kwezakhiwo zedatha ezisebenza kahle (njengezihlahla noma amathebula e-hashi), nama-algorithms adizayinelwe ngokuqondile idatha enkulu, njenge-MapReduce.

I-athikili ehlobene:

Iyini i-Algorithm Evamile futhi Kungani Kufanele Unakekele?