{"id":30936,"date":"2019-10-31T21:38:20","date_gmt":"2019-10-31T18:38:20","guid":{"rendered":"https:\/\/prohoster.info\/blog\/mashinnoe-obuchenie-bez-python-anaconda-i-prochih-presmykayushhihsya\/"},"modified":"2019-10-31T21:38:20","modified_gmt":"2019-10-31T18:38:20","slug":"mashinnoe-obuchenie-bez-python-anaconda-i-prochih-presmykayushhihsya","status":"publish","type":"post","link":"https:\/\/prohoster.info\/et\/blog\/news\/mashinnoe-obuchenie-bez-python-anaconda-i-prochih-presmykayushhihsya","title":{"rendered":"Masin\u00f5pe ilma Pythonita, Anacondata ja muude madude","gt_translate_keys":[{"key":"rendered","format":"text"}]},"content":{"rendered":"<p>Ei, ma muidugi ei m\u00f5tle t\u00f5siselt. Peab ju olema mingi piir, kui palju saab teemat lihtsustada. Kuid algfaasis, peamiste kontseptsioonide m\u00f5istmiseks ja kiireks teemaga tutvumiseks v\u00f5ib-olla on see lubatav. Ja millise nimega seda materjali \u00f5igesti nimetada (variandid: \u201eMasin\u00f5pe algajatele\u201c, \u201eAndmete anal\u00fc\u00fcs algusest peale\u201c, \u201eAlgoritmid k\u00f5ige v\u00e4iksematele\u201c), arutame hiljem. <\/p>\n<p>Asume siis asja juurde. Olen koostanud mitmeid rakenduste programme MS Excelis protsesside visualiseerimiseks ja selgeks j\u00f5udmiseks, mis toimuvad erinevates masin\u00f5ppe meetodites andmete anal\u00fc\u00fcsimisel. Lood on veidigi uskumatud, nagu \u00fctlevad kultuuri esindajad, kes on v\u00e4lja t\u00f6\u00f6tanud enamik neist meetoditest (muide, mitte k\u00f5ik. V\u00f5imas \u201etoetavate vektorite meetod\u201c ehk SVM \u2013 toetav vektormasin \u2013 on meie kaasmaalase Vladimir Vapnik\u2019i leiutis, Moskva Juhtimisinstituut. 1963. aasta, muide! Praegu \u00f5petab ja t\u00f6\u00f6tab ta aga Ameerikas).<\/p>\n<p>Kolm faili tutvumiseks<br \/>\n<noindex><a rel=\"nofollow\" name=\"habracut\"><\/a><\/noindex><\/p>\n<h2>1. K-meetoditega klasterdamine<\/h2>\n<p>\nSelliste \u00fclesannete liik kuulub \u201e\u00f5petamata \u00f5ppimise\u201d alla, kui peame jagama esialgsed andmed teatud eelnevalt tuntud kategooriate arvuks, kuid meil ei ole k\u00fcllalt \u201e\u00f5igeid vastuseid\u201d, need tuleb andmetest v\u00e4lja t\u00f6\u00f6tada. Alustav klassikaline \u00fclesanne iiriste liikide m\u00e4\u00e4ramine (Ronald Fisher, 1936. aasta!), mis loetakse selle teadmiste valdkonna esimeseks etapiks \u2013 on just sellise olemusega.<\/p>\n<p>Meetod on piisavalt lihtne. Meil on objektiloend, mis on esitatud vektoritena (N numbrite kogum). Iiristel on see \u2013 kogum 4 numbrit, mis iseloomustavad lille: \u00f5ie v\u00e4lise ja sisemise osade pikkus ja laius, vastavalt (<noindex><a rel=\"nofollow\" href=\"https:\/\/ru.wikipedia.org\/wiki\/%D0%98%D1%80%D0%B8%D1%81%D1%8B_%D0%A4%D0%B8%D1%88%D0%B5%D1%80%D0%B0\">Iirised Fisher \u2013 Vikipeedia<\/a><\/noindex>). Objektide vahelise kauguse v\u00f5i sarnasuse meetodina valitakse tavaline Dekarti meetrika.<\/p>\n<p>J\u00e4rgmiseks valitakse juhuslikult (v\u00f5i mitte juhuslikult, vaata edasi) klastrite keskpunktid ning arvutatakse iga objekti kaugus klastrite keskpunktidest. Iga objekt m\u00e4rgitakse selle iteratsiooni sammul kuuluvaks sellele l\u00e4himale keskpunktile. Seej\u00e4rel liigutatakse iga klastrikeskuse kohta oma liikmete koordinaatide aritmeetiline keskpunkt (f\u00fc\u00fcsikas nimetatakse seda ka \u201emassikeskuseks\u201d) ja protseduur kordub.<\/p>\n<p>Protsess konvergeerub piisavalt kiiresti. Kahem\u00f5\u00f5tmeliselt n\u00e4eb see v\u00e4lja nii:<\/p>\n<p>1. Algne juhuslik punktide jaotumine tasandil ning klastrite arv<\/p>\n<p><img decoding=\"async\" alt=\"Masin\u00f5pe ilma Pythonita, Anacondata ja muude madude\" src=\"\/wp-content\/uploads\/2019\/04\/98afc213ffcfa702527d1977b5160428.jpg\" style=\"display:block;margin: 0 auto;\" \/><br \/>\n<br \/>\n2. Klastrite keskpunktide m\u00e4\u00e4ramine ja punktide m\u00e4\u00e4ramine oma klastritesse<\/p>\n<p><img decoding=\"async\" alt=\"Masin\u00f5pe ilma Pythonita, Anacondata ja muude madude\" src=\"\/wp-content\/uploads\/2019\/04\/268dbf902b225ea700e401ab6ef06c2d.jpg\" style=\"display:block;margin: 0 auto;\" \/><br \/>\n<br \/>\n3. Klastrite keskpunktide koordinaatide \u00fcmberpaigutamine, punktide kuuluvuse \u00fcmberarvestamine, kuni keskpunktid stabiliseeruvad. On n\u00e4ha klastrite keskuste liikumisteed l\u00f5ppasendisse.<\/p>\n<p><img decoding=\"async\" alt=\"Masin\u00f5pe ilma Pythonita, Anacondata ja muude madude\" src=\"\/wp-content\/uploads\/2019\/04\/59393621525594066943e444d98b81b3.jpg\" style=\"display:block;margin: 0 auto;\" \/><br \/>\n<br \/>\nIgal hetkel on v\u00f5imalik m\u00e4\u00e4rata uusi klastrite keskpunkte (ilma uue punktide jaotuse genereerimiseta!) ja n\u00e4ha, et protsess ei ole alati \u00fcheselt m\u00f5istetav. Matemaatiliselt t\u00e4hendab see, et optimeeritava funktsiooni (punktide kauguste ruutude summad oma klastrite keskpunktidest) puhul leiame me mitte globaalset, vaid lokaalse miinimumi. Selle probleemi lahendamiseks v\u00f5ib kas valida mittejuhuslikud algset keskpunktid v\u00f5i proovida erinevaid keskpunktide kombinatsioone (m\u00f5nikord on kasulik need paigutada t\u00e4pselt m\u00f5nda punktidesse, siis on v\u00e4hemalt kindel, et me ei saa t\u00fchje klastreid). Igatahes on l\u00f5pliku kogumi puhul alati t\u00e4pne alumine piir. <\/p>\n<p><noindex><a rel=\"nofollow\" href=\"http:\/\/wit.ru\/habr\/K-means.zip\">Selle failiga saab m\u00e4ngida sellel lingil<\/a><\/noindex> (\u00e4rge unustage lubada makrode toetust. Failid on viiruste suhtes kontrollitud)<\/p>\n<p>Meetodi kirjeldus Vikipeedias \u2014 <noindex><a rel=\"nofollow\" href=\"https:\/\/ru.wikipedia.org\/wiki\/%D0%9C%D0%B5%D1%82%D0%BE%D0%B4_k-%D1%81%D1%80%D0%B5%D0%B4%D0%BD%D0%B8%D1%85\">k-ennustuste meetod<\/a><\/noindex><\/p>\n<h2>2. Pol\u00fcnoomide ligikaudne hindamine ja andmete jagamine. \u00dclekoolitus<\/h2>\n<p>\nImetlusv\u00e4\u00e4rne teadlane ja andmete teaduse populariseerija K.V. Vorontsov r\u00e4\u00e4gib l\u00fchidalt masin\u00f5ppemeetoditest kui \"k\u00f5verate joonistamisest punktide kaudu\". Selles n\u00e4ites selgitame andmete mustrite leidmist v\u00e4ikeste ruutude meetodi abil. <\/p>\n<p>On n\u00e4idatud andmete jagamise tehnika \"\u00f5ppimis\" ja \"kontroll\" r\u00fchmadesse, samuti n\u00e4htust, mida tuntakse kui \u00fclekoolitamine. \u00d5ige ligikaudse hindamise korral on meil teatud viga \u00f5ppimisandmetes ja veidi suurem viga kontrollandmetes. Vale hindamisega on t\u00e4pne sobitamine \u00f5ppimisandmetele ja tohutu viga kontrollandmetes.<\/p>\n<p>(Tuntud on fakt, et N punkti kaudu saab joonistada ainulaadse N-1 astme k\u00f5vera, ja see meetod ei anna \u00fcldjuhul soovitud tulemust. <noindex><a rel=\"nofollow\" href=\"https:\/\/ru.wikipedia.org\/wiki\/%D0%98%D0%BD%D1%82%D0%B5%D1%80%D0%BF%D0%BE%D0%BB%D1%8F%D1%86%D0%B8%D0%BE%D0%BD%D0%BD%D1%8B%D0%B9_%D0%BC%D0%BD%D0%BE%D0%B3%D0%BE%D1%87%D0%BB%D0%B5%D0%BD_%D0%9B%D0%B0%D0%B3%D1%80%D0%B0%D0%BD%D0%B6%D0%B0\">Lagrange'i interpoleeriv pol\u00fcnoom Vikipeedias<\/a><\/noindex>)<\/p>\n<p>1. M\u00e4\u00e4rame esialgse jaotuse<\/p>\n<p><img decoding=\"async\" alt=\"Masin\u00f5pe ilma Pythonita, Anacondata ja muude madude\" src=\"\/wp-content\/uploads\/2019\/04\/617cd8456d91a4294803f979f98a3ef0.jpg\" style=\"display:block;margin: 0 auto;\" \/><br \/>\n<br \/>\n2. Jagame punktid \"\u00f5ppimis\" ja \"kontroll\" r\u00fchmadesse suhtega 70:30.<\/p>\n<p><img decoding=\"async\" alt=\"Masin\u00f5pe ilma Pythonita, Anacondata ja muude madude\" src=\"\/wp-content\/uploads\/2019\/04\/5211af73ace8c254b44a234a2812b586.jpg\" style=\"display:block;margin: 0 auto;\" \/><br \/>\n<br \/>\n3. Joonistame approximatiivse k\u00f5vera \u00f5petamispunktide kaudu, n\u00e4eme viga, mille ta kontrollandmetel annab.<\/p>\n<p><img decoding=\"async\" alt=\"Masin\u00f5pe ilma Pythonita, Anacondata ja muude madude\" src=\"\/wp-content\/uploads\/2019\/04\/c26e0bed0959aeb30723f67bafc3b58c.jpg\" style=\"display:block;margin: 0 auto;\" \/><br \/>\n<br \/>\n4. Joonistame t\u00e4pse k\u00f5vera \u00f5petamispunktide kaudu ja n\u00e4eme kohutavat viga kontrollandmetel (ja nulli \u00f5petamispunktidel, aga mis sellest kasu on?).<\/p>\n<p><img decoding=\"async\" alt=\"Masin\u00f5pe ilma Pythonita, Anacondata ja muude madude\" src=\"\/wp-content\/uploads\/2019\/04\/dbc34251e6444093805b10c56ee62eae.jpg\" style=\"display:block;margin: 0 auto;\" \/><br \/>\n<br \/>\nN\u00e4idatud on muidugi k\u00f5ige lihtsam variant, millel on ainsad jaotused \"\u00f5petamise\" ja \"kontrolli\" alamgruppidesse, \u00fcldjuhul tehakse seda korduvalt parimate koefitsientide seadistamiseks.<\/p>\n<p><noindex><a rel=\"nofollow\" href=\"http:\/\/wit.ru\/habr\/Lagrange.Approximation.zip\">Fail on siin saadaval, kontrollitud viiruset\u00f5rjega.<\/a><\/noindex> Palun l\u00fclitage makrod sisse, et see \u00f5igesti t\u00f6\u00f6taks.<\/p>\n<h2>3. Gradientne langemine ja vea muutumise d\u00fcnaamika.<\/h2>\n<p>\nSiin on 4-m\u00f5\u00f5tmeline juhtum ja lineaarsed regressioonid. Lineaarsete regressioonide koefitsiendid m\u00e4\u00e4ratakse sammude kaudu gradientsete langemismeetodi abil, alguses on k\u00f5ik koefitsiendid nullid. Eraldi graafik n\u00e4itab vea v\u00e4henemise d\u00fcnaamikat, kui koefitsiente \u00fcha t\u00e4psemalt seadistatakse. On v\u00f5imalus vaadata k\u00f5iki nelja 2-m\u00f5\u00f5tmelist projektsiooni.<\/p>\n<p>Kui seadistada liiga suur gradientse langemise samm, siis on n\u00e4ha, et igal korral me h\u00fcppame miinimumist \u00fcle ja tulemusele j\u00f5uame rohkemate sammudega, kuigi l\u00f5puks me k\u00f5ik \u00fcheselt siiski j\u00f5uame (kui ainult me ei t\u00f5sta langemise sammu liiga palju - siis algoritm p\u00e4rast enam ei t\u00f6\u00f6ta). Ja graafik vea s\u00f5ltuvusest iteratsiooni sammust ei ole sujuv, vaid \"t\u00f5mblev\".<\/p>\n<p>1. Genererime andmed, seame gradientse langemise sammu.<\/p>\n<p><img decoding=\"async\" alt=\"Masin\u00f5pe ilma Pythonita, Anacondata ja muude madude\" src=\"\/wp-content\/uploads\/2019\/04\/0bb3db030accff0003e6c49c328817c5.jpg\" style=\"display:block;margin: 0 auto;\" \/><br \/>\n<br \/>\n2. \u00d5ige gradientse langemise sammu valimisega j\u00f5uame sujuvalt ja piisavalt kiiresti miinimumini.<\/p>\n<p><img decoding=\"async\" alt=\"Masin\u00f5pe ilma Pythonita, Anacondata ja muude madude\" src=\"\/wp-content\/uploads\/2019\/04\/ecaaf01cff37d60f10174edbe1dbf0f2.jpg\" style=\"display:block;margin: 0 auto;\" \/><br \/>\n<br \/>\n3. Vale gradientse langemise sammu valimisega h\u00fcppame maksimumist \u00fcle, vea graafik on \"t\u00f5mblev\", konvergents v\u00f5tab rohkem samme.<\/p>\n<p><img decoding=\"async\" alt=\"Masin\u00f5pe ilma Pythonita, Anacondata ja muude madude\" src=\"\/wp-content\/uploads\/2019\/04\/4adc84919a263a034a5ef0913c08266e.jpg\" style=\"display:block;margin: 0 auto;\" \/><br \/>\nja<\/p>\n<p><img decoding=\"async\" alt=\"Masin\u00f5pe ilma Pythonita, Anacondata ja muude madude\" src=\"\/wp-content\/uploads\/2019\/04\/9d2befa6c9c6ac10211635c95ad82040.jpg\" style=\"display:block;margin: 0 auto;\" \/><br \/>\n<br \/>\n4. \u00c4\u00e4rmiselt vale gradientse langemise sammu valimisega eemaldume miinimumist.<\/p>\n<p><img decoding=\"async\" alt=\"Masin\u00f5pe ilma Pythonita, Anacondata ja muude madude\" src=\"\/wp-content\/uploads\/2019\/04\/6ed347695683d0403778f32052ace050.jpg\" style=\"display:block;margin: 0 auto;\" \/><br \/>\n<br \/>\n(Protsessi kordamiseks n\u00e4idatud gradientse langemise sammu v\u00e4\u00e4rtustega, palun valige \"standardandmed\").<\/p>\n<p><noindex><a rel=\"nofollow\" href=\"http:\/\/wit.ru\/habr\/Linear.Regerssion.zip\">Fail - selle lingi kaudu, peate makrosid sisse l\u00fclitama, viiruseid pole.<\/a><\/noindex><\/p>\n<p><b>Kuidas arvab austatud kogukond, kas selline lihtsustamine ja materjali esitamise meetod on lubatud? Kas tasub artikkel inglise keelde t\u00f5lkida? <\/b><br \/>\n<br \/>Allikas: <a content=\"nofollow\" rel=\"nofollow\" href=\"https:\/\/habr.com\/ru\/post\/446150\/\">habr.com<\/a><\/p>","protected":false,"gt_translate_keys":[{"key":"rendered","format":"html"}]},"excerpt":{"rendered":"<p>\u041d\u0435\u0442, \u043d\u0443 \u044f, \u043a\u043e\u043d\u0435\u0447\u043d\u043e, \u043d\u0435 \u0432\u0441\u0435\u0440\u044c\u0435\u0437. \u0414\u043e\u043b\u0436\u0435\u043d \u0436\u0435 \u0431\u044b\u0442\u044c \u043f\u0440\u0435\u0434\u0435\u043b, \u0434\u043e \u043a\u0430\u043a\u043e\u0439 \u0441\u0442\u0435\u043f\u0435\u043d\u0438 \u0432\u043e\u0437\u043c\u043e\u0436\u043d\u043e \u0443\u043f\u0440\u043e\u0449\u0430\u0442\u044c \u043f\u0440\u0435\u0434\u043c\u0435\u0442. \u041d\u043e \u0434\u043b\u044f \u043f\u0435\u0440\u0432\u044b\u0445 \u044d\u0442\u0430\u043f\u043e\u0432, \u043f\u043e\u043d\u0438\u043c\u0430\u043d\u0438\u044f \u0431\u0430\u0437\u043e\u0432\u044b\u0445 \u043a\u043e\u043d\u0446\u0435\u043f\u0446\u0438\u0439 \u0438 \u0431\u044b\u0441\u0442\u0440\u043e\u0433\u043e \u00ab\u0432\u044a\u0435\u0437\u0436\u0430\u043d\u0438\u044f\u00bb \u0432 \u0442\u0435\u043c\u0443, \u043c\u043e\u0436\u0435\u0442 \u0431\u044b\u0442\u044c, \u0438 \u0434\u043e\u043f\u0443\u0441\u0442\u0438\u043c\u043e. \u0410 \u043a\u0430\u043a \u043f\u0440\u0430\u0432\u0438\u043b\u044c\u043d\u043e \u043f\u043e\u0438\u043c\u0435\u043d\u043e\u0432\u0430\u0442\u044c \u0434\u0430\u043d\u043d\u044b\u0439 \u043c\u0430\u0442\u0435\u0440\u0438\u0430\u043b (\u0432\u0430\u0440\u0438\u0430\u043d\u0442\u044b: \u00ab\u041c\u0430\u0448\u0438\u043d\u043d\u043e\u0435 \u043e\u0431\u0443\u0447\u0435\u043d\u0438\u0435 \u0434\u043b\u044f \u0447\u0430\u0439\u043d\u0438\u043a\u043e\u0432\u00bb, \u00ab\u0410\u043d\u0430\u043b\u0438\u0437 \u0434\u0430\u043d\u043d\u044b\u0445 \u0441 \u043f\u0435\u043b\u0435\u043d\u043e\u043a\u00bb, \u00ab\u0410\u043b\u0433\u043e\u0440\u0438\u0442\u043c\u044b \u0434\u043b\u044f \u0441\u0430\u043c\u044b\u0445 \u043c\u0430\u043b\u0435\u043d\u044c\u043a\u0438\u0445\u00bb), \u043e\u0431\u0441\u0443\u0434\u0438\u043c \u0432 \u043a\u043e\u043d\u0446\u0435. \u041a [&hellip;]<\/p>\n","protected":false,"gt_translate_keys":[{"key":"rendered","format":"html"}]},"author":1,"featured_media":22912,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[702],"tags":[],"class_list":["post-30936","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-news"],"aioseo_notices":[],"aioseo_head":"\n\t\t<!-- All in One SEO 5.0.1.1 - aioseo.com -->\n\t<meta name=\"description\" content=\"\u041d\u0435\u0442, \u043d\u0443 \u044f, \u043a\u043e\u043d\u0435\u0447\u043d\u043e, \u043d\u0435 \u0432\u0441\u0435\u0440\u044c\u0435\u0437. \u0414\u043e\u043b\u0436\u0435\u043d \u0436\u0435 \u0431\u044b\u0442\u044c \u043f\u0440\u0435\u0434\u0435\u043b, \u0434\u043e \u043a\u0430\u043a\u043e\u0439 \u0441\u0442\u0435\u043f\u0435\u043d\u0438 \u0432\u043e\u0437\u043c\u043e\u0436\u043d\u043e \u0443\u043f\u0440\u043e\u0449\u0430\u0442\u044c \u043f\u0440\u0435\u0434\u043c\u0435\u0442. \u041d\u043e \u0434\u043b\u044f \u043f\u0435\u0440\u0432\u044b\u0445 \u044d\u0442\u0430\u043f\u043e\u0432, \u043f\u043e\u043d\u0438\u043c\u0430\u043d\u0438\u044f \u0431\u0430\u0437\u043e\u0432\u044b\u0445 \u043a\u043e\u043d\u0446\u0435\u043f\u0446\u0438\u0439 \u0438 \u0431\u044b\u0441\u0442\u0440\u043e\u0433\u043e \u00ab\u0432\u044a\u0435\u0437\u0436\u0430\u043d\u0438\u044f\u00bb \u0432 \u0442\u0435\u043c\u0443, \u043c\u043e\u0436\u0435\u0442 \u0431\u044b\u0442\u044c, \u0438 \u0434\u043e\u043f\u0443\u0441\u0442\u0438\u043c\u043e.\" \/>\n\t<meta name=\"robots\" content=\"max-image-preview:large\" \/>\n\t<meta name=\"author\" content=\"Yuri Gagarin\"\/>\n\t<link rel=\"canonical\" href=\"https:\/\/prohoster.info\/et\/blog\/news\/mashinnoe-obuchenie-bez-python-anaconda-i-prochih-presmykayushhihsya\" \/>\n\t<meta name=\"generator\" content=\"All in One SEO (AIOSEO) 5.0.1.1\" \/>\n\t\t<meta property=\"og:locale\" content=\"et_EE\" \/>\n\t\t<meta property=\"og:site_name\" content=\"ProHoster | \u041a\u0443\u043f\u0438\u0442\u044c \u043d\u0430\u0434\u0435\u0436\u043d\u044b\u0439 \u0445\u043e\u0441\u0442\u0438\u043d\u0433 \u0434\u043b\u044f \u0441\u0430\u0439\u0442\u043e\u0432 \u0441 \u0437\u0430\u0449\u0438\u0442\u043e\u0439 \u043e\u0442 DDoS, VPS VDS \u0441\u0435\u0440\u0432\u0435\u0440\u044b\" \/>\n\t\t<meta property=\"og:type\" content=\"article\" \/>\n\t\t<meta property=\"og:title\" content=\"\ud83e\udd47\u041c\u0430\u0448\u0438\u043d\u043d\u043e\u0435 \u043e\u0431\u0443\u0447\u0435\u043d\u0438\u0435 \u0431\u0435\u0437 Python, Anaconda \u0438 \u043f\u0440\u043e\u0447\u0438\u0445 \u043f\u0440\u0435\u0441\u043c\u044b\u043a\u0430\u044e\u0449\u0438\u0445\u0441\u044f | ProHoster\" \/>\n\t\t<meta property=\"og:description\" content=\"\u041d\u0435\u0442, \u043d\u0443 \u044f, \u043a\u043e\u043d\u0435\u0447\u043d\u043e, \u043d\u0435 \u0432\u0441\u0435\u0440\u044c\u0435\u0437. \u0414\u043e\u043b\u0436\u0435\u043d \u0436\u0435 \u0431\u044b\u0442\u044c \u043f\u0440\u0435\u0434\u0435\u043b, \u0434\u043e \u043a\u0430\u043a\u043e\u0439 \u0441\u0442\u0435\u043f\u0435\u043d\u0438 \u0432\u043e\u0437\u043c\u043e\u0436\u043d\u043e \u0443\u043f\u0440\u043e\u0449\u0430\u0442\u044c \u043f\u0440\u0435\u0434\u043c\u0435\u0442. \u041d\u043e \u0434\u043b\u044f \u043f\u0435\u0440\u0432\u044b\u0445 \u044d\u0442\u0430\u043f\u043e\u0432, \u043f\u043e\u043d\u0438\u043c\u0430\u043d\u0438\u044f \u0431\u0430\u0437\u043e\u0432\u044b\u0445 \u043a\u043e\u043d\u0446\u0435\u043f\u0446\u0438\u0439 \u0438 \u0431\u044b\u0441\u0442\u0440\u043e\u0433\u043e \u00ab\u0432\u044a\u0435\u0437\u0436\u0430\u043d\u0438\u044f\u00bb \u0432 \u0442\u0435\u043c\u0443, \u043c\u043e\u0436\u0435\u0442 \u0431\u044b\u0442\u044c, \u0438 \u0434\u043e\u043f\u0443\u0441\u0442\u0438\u043c\u043e.\" \/>\n\t\t<meta property=\"og:url\" content=\"https:\/\/prohoster.info\/et\/blog\/news\/mashinnoe-obuchenie-bez-python-anaconda-i-prochih-presmykayushhihsya\" \/>\n\t\t<meta property=\"og:image\" content=\"https:\/\/prohoster.info\/wp-content\/uploads\/2021\/11\/logo-350.jpg\" \/>\n\t\t<meta property=\"og:image:secure_url\" content=\"https:\/\/prohoster.info\/wp-content\/uploads\/2021\/11\/logo-350.jpg\" \/>\n\t\t<meta property=\"og:image:width\" content=\"350\" \/>\n\t\t<meta property=\"og:image:height\" content=\"350\" \/>\n\t\t<meta property=\"article:published_time\" content=\"2019-10-31T18:38:20+00:00\" \/>\n\t\t<meta property=\"article:modified_time\" content=\"2019-10-31T18:38:20+00:00\" \/>\n\t\t<meta property=\"article:publisher\" content=\"https:\/\/www.facebook.com\/prohoster\" \/>\n\t\t<meta property=\"article:author\" content=\"https:\/\/www.facebook.com\/prohoster\" \/>\n\t\t<!-- All in One SEO -->\n\n","aioseo_head_json":{"title":"\ud83e\udd47Masin\u00f5pe ilma Pythoni, Anaconda ja muude roomajadeta | ProHoster","description":"Ei, noh, ma, muidugi, ei m\u00f5tle sellele t\u00f5siselt. Peab olema piir, kui kaugele on v\u00f5imalik teemat lihtsustada. Kuid esimestel etappidel, p\u00f5hikontseptsioonide m\u00f5istmisel ja kiirel teema \"sisseelamisel\", v\u00f5ib see olla lubatud.","canonical_url":"https:\/\/prohoster.info\/et\/blog\/news\/mashinnoe-obuchenie-bez-python-anaconda-i-prochih-presmykayushhihsya","robots":"max-image-preview:large","keywords":"","webmasterTools":{"miscellaneous":""},"schema":null,"og:locale":"et_EE","og:site_name":"ProHoster | \u041a\u0443\u043f\u0438\u0442\u044c \u043d\u0430\u0434\u0435\u0436\u043d\u044b\u0439 \u0445\u043e\u0441\u0442\u0438\u043d\u0433 \u0434\u043b\u044f \u0441\u0430\u0439\u0442\u043e\u0432 \u0441 \u0437\u0430\u0449\u0438\u0442\u043e\u0439 \u043e\u0442 DDoS, VPS VDS \u0441\u0435\u0440\u0432\u0435\u0440\u044b","og:type":"article","og:title":"\ud83e\udd47\u041c\u0430\u0448\u0438\u043d\u043d\u043e\u0435 \u043e\u0431\u0443\u0447\u0435\u043d\u0438\u0435 \u0431\u0435\u0437 Python, Anaconda \u0438 \u043f\u0440\u043e\u0447\u0438\u0445 \u043f\u0440\u0435\u0441\u043c\u044b\u043a\u0430\u044e\u0449\u0438\u0445\u0441\u044f | ProHoster","og:description":"\u041d\u0435\u0442, \u043d\u0443 \u044f, \u043a\u043e\u043d\u0435\u0447\u043d\u043e, \u043d\u0435 \u0432\u0441\u0435\u0440\u044c\u0435\u0437. \u0414\u043e\u043b\u0436\u0435\u043d \u0436\u0435 \u0431\u044b\u0442\u044c \u043f\u0440\u0435\u0434\u0435\u043b, \u0434\u043e \u043a\u0430\u043a\u043e\u0439 \u0441\u0442\u0435\u043f\u0435\u043d\u0438 \u0432\u043e\u0437\u043c\u043e\u0436\u043d\u043e \u0443\u043f\u0440\u043e\u0449\u0430\u0442\u044c \u043f\u0440\u0435\u0434\u043c\u0435\u0442. \u041d\u043e \u0434\u043b\u044f \u043f\u0435\u0440\u0432\u044b\u0445 \u044d\u0442\u0430\u043f\u043e\u0432, \u043f\u043e\u043d\u0438\u043c\u0430\u043d\u0438\u044f \u0431\u0430\u0437\u043e\u0432\u044b\u0445 \u043a\u043e\u043d\u0446\u0435\u043f\u0446\u0438\u0439 \u0438 \u0431\u044b\u0441\u0442\u0440\u043e\u0433\u043e \u00ab\u0432\u044a\u0435\u0437\u0436\u0430\u043d\u0438\u044f\u00bb \u0432 \u0442\u0435\u043c\u0443, \u043c\u043e\u0436\u0435\u0442 \u0431\u044b\u0442\u044c, \u0438 \u0434\u043e\u043f\u0443\u0441\u0442\u0438\u043c\u043e.","og:url":"https:\/\/prohoster.info\/et\/blog\/news\/mashinnoe-obuchenie-bez-python-anaconda-i-prochih-presmykayushhihsya","og:image":"https:\/\/prohoster.info\/wp-content\/uploads\/2021\/11\/logo-350.jpg","og:image:secure_url":"https:\/\/prohoster.info\/wp-content\/uploads\/2021\/11\/logo-350.jpg","og:image:width":350,"og:image:height":350,"article:published_time":"2019-10-31T18:38:20+00:00","article:modified_time":"2019-10-31T18:38:20+00:00","article:publisher":"https:\/\/www.facebook.com\/prohoster","article:author":"https:\/\/www.facebook.com\/prohoster"},"aioseo_meta_data":{"post_id":"30936","title":null,"description":null,"keywords":null,"keyphrases":null,"primary_term":null,"canonical_url":null,"og_title":null,"og_description":null,"og_object_type":"default","og_image_type":"default","og_image_url":null,"og_image_width":null,"og_image_height":null,"og_image_custom_url":null,"og_image_custom_fields":null,"og_video":null,"og_custom_url":null,"og_article_section":null,"og_article_tags":null,"twitter_use_og":false,"twitter_card":"default","twitter_image_type":"default","twitter_image_url":null,"twitter_image_custom_url":null,"twitter_image_custom_fields":null,"twitter_title":null,"twitter_description":null,"schema":{"blockGraphs":[],"customGraphs":[],"default":{"data":{"Article":[],"Course":[],"Dataset":[],"FAQPage":[],"Movie":[],"Person":[],"Product":[],"ProductReview":[],"Car":[],"Recipe":[],"Service":[],"SoftwareApplication":[],"WebPage":[]},"graphName":"","isEnabled":true},"graphs":[]},"schema_type":null,"schema_type_options":null,"pillar_content":false,"robots_default":true,"robots_noindex":false,"robots_noarchive":false,"robots_nosnippet":false,"robots_nofollow":false,"robots_noimageindex":false,"robots_noodp":false,"robots_notranslate":false,"robots_max_snippet":null,"robots_max_videopreview":null,"robots_max_imagepreview":"large","priority":null,"frequency":null,"local_seo":null,"seo_analyzer_scan_date":"2026-01-21 03:45:19","breadcrumb_settings":null,"limit_modified_date":false,"reviewed_by":null,"ai":null,"created":"2021-03-01 03:27:05","updated":"2026-01-21 03:45:19","focus_keyword":null,"additional_keywords":null,"truseo_locale":null},"gt_translate_keys":[{"key":"link","format":"url"}],"_links":{"self":[{"href":"https:\/\/prohoster.info\/et\/wp-json\/wp\/v2\/posts\/30936","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/prohoster.info\/et\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/prohoster.info\/et\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/prohoster.info\/et\/wp-json\/wp\/v2\/users\/1"}],"replies":[{"embeddable":true,"href":"https:\/\/prohoster.info\/et\/wp-json\/wp\/v2\/comments?post=30936"}],"version-history":[{"count":0,"href":"https:\/\/prohoster.info\/et\/wp-json\/wp\/v2\/posts\/30936\/revisions"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/prohoster.info\/et\/wp-json\/wp\/v2\/media\/22912"}],"wp:attachment":[{"href":"https:\/\/prohoster.info\/et\/wp-json\/wp\/v2\/media?parent=30936"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/prohoster.info\/et\/wp-json\/wp\/v2\/categories?post=30936"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/prohoster.info\/et\/wp-json\/wp\/v2\/tags?post=30936"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}