{"id":6620,"date":"2024-06-06T11:04:17","date_gmt":"2024-06-06T11:04:17","guid":{"rendered":"http:\/\/the-codest.localhost\/dictionary\/machine-learning\/"},"modified":"2024-06-06T11:04:17","modified_gmt":"2024-06-06T11:04:17","slug":"koneoppiminen","status":"publish","type":"dictionary","link":"https:\/\/thecodest.co\/fi\/dictionary\/machine-learning\/","title":{"rendered":"Machine Learning"},"content":{"rendered":"<h1>Machine Learning<\/h1>\n<p><a href=\"https:\/\/thecodest.co\/fi\/blog\/banks-go-high-tech-unravel-fraud-with-machine-learning\/\">Machine Learning<\/a> on teko\u00e4lyn osa-alue (<a href=\"https:\/\/thecodest.co\/fi\/blog\/the-rise-of-ai-in-the-baltics-discussion-on-estonia-latvia-and-lithuanias-tech-scene\/\">AI<\/a>), jossa keskityt\u00e4\u00e4n sellaisten algoritmien ja tilastollisten mallien kehitt\u00e4miseen, joiden avulla tietokonej\u00e4rjestelm\u00e4t voivat oppia ja kehitty\u00e4 kokemuksen perusteella ilman nimenomaista ohjelmointia. Siihen liittyy monimutkaisten matemaattisten ja tilastollisten tekniikoiden k\u00e4ytt\u00f6 suurten tietokokonaisuuksien analysoimiseksi ja tulkitsemiseksi, mallien tunnistamiseksi ja ennusteiden tai p\u00e4\u00e4t\u00f6sten tekemiseksi niiden perusteella. <a href=\"https:\/\/thecodest.co\/fi\/blog\/app-data-collection-security-risks-value-and-types-explored\/\">tiedot<\/a>.<\/p>\n<p>Machine Learning:n tavoitteena on luoda \u00e4lykk\u00e4it\u00e4 j\u00e4rjestelmi\u00e4, jotka oppivat automaattisesti ja kehittyv\u00e4t kokemuksen perusteella ilman ihmisen puuttumista asiaan. T\u00e4m\u00e4 saavutetaan kouluttamalla j\u00e4rjestelm\u00e4\u00e4 suurilla tietom\u00e4\u00e4rill\u00e4, jolloin se pystyy tunnistamaan kuvioita ja suhteita ja k\u00e4ytt\u00e4m\u00e4\u00e4n t\u00e4t\u00e4 tietoa ennusteiden tai p\u00e4\u00e4t\u00f6sten tekemiseen uusien tietojen perusteella.<\/p>\n<p>Machine Learning voidaan jakaa karkeasti kolmeen luokkaan:<\/p>\n<ul>\n<li><b>Valvottu oppiminen:<\/b> T\u00e4ss\u00e4 yhteydess\u00e4 k\u00e4ytet\u00e4\u00e4n merkittyj\u00e4 tietoja mallin kouluttamiseen ennusteiden tai p\u00e4\u00e4t\u00f6sten tekemist\u00e4 varten. J\u00e4rjestelm\u00e4lle annetaan sy\u00f6tt\u00f6tiedot ja vastaavat l\u00e4ht\u00f6tiedot, ja se oppii yhdist\u00e4m\u00e4\u00e4n sy\u00f6tteen ja tuloksen tunnistamalla tiedoissa olevia malleja ja suhteita. Esimerkkej\u00e4 valvotusta oppimisesta ovat kuvantunnistus, puheentunnistus ja luonnollisen kielen k\u00e4sittely.<\/li>\n<li><b>Valvomaton oppiminen:<\/b> T\u00e4ss\u00e4 k\u00e4ytet\u00e4\u00e4n merkitsem\u00e4t\u00f6nt\u00e4 dataa mallin kouluttamiseen, jotta datasta voidaan tunnistaa kuvioita ja suhteita. J\u00e4rjestelm\u00e4 saa sy\u00f6tt\u00f6tiedot, ja se oppii ryhmittelem\u00e4\u00e4n ja klusteroimaan tiedot samankaltaisuuksien ja erojen perusteella. Esimerkkej\u00e4 valvomattomasta oppimisesta ovat klusterointi, poikkeamien havaitseminen ja dimensioiden pienent\u00e4minen.<\/li>\n<li><b>Vahvistusoppiminen:<\/b> T\u00e4ss\u00e4 k\u00e4ytet\u00e4\u00e4n palkitsemiseen perustuvaa j\u00e4rjestelm\u00e4\u00e4 mallin kouluttamiseksi tekem\u00e4\u00e4n p\u00e4\u00e4t\u00f6ksi\u00e4 ja toteuttamaan toimia. J\u00e4rjestelm\u00e4lle annetaan joukko mahdollisia toimia ja palkitsemisfunktio, ja se oppii maksimoimaan palkkion tekem\u00e4ll\u00e4 parhaat mahdolliset toimet tietyss\u00e4 tilanteessa. Esimerkkej\u00e4 vahvistusoppimisesta ovat pelaaminen, robotiikka ja autonomiset ajoneuvot.<\/li>\n<\/ul>\n<p>Machine Learning:ll\u00e4 on laaja valikoima sovelluksia eri teollisuudenaloilla, kuten seuraavilla aloilla <a href=\"https:\/\/thecodest.co\/fi\/blog\/healthcare-softwares-types-use-cases\/\">terveydenhuolto<\/a>, <a href=\"https:\/\/thecodest.co\/fi\/blog\/top-technologies-used-in-european-fintech-development\/\">rahoitus<\/a>, v\u00e4hitt\u00e4iskauppa ja <a href=\"https:\/\/thecodest.co\/fi\/dictionary\/manufacturing-software-development\/\">valmistus<\/a>. Sit\u00e4 k\u00e4ytet\u00e4\u00e4n asiakaskokemuksen parantamiseen, liiketoimintaprosessien optimointiin sek\u00e4 tarkempien ennusteiden ja p\u00e4\u00e4t\u00f6sten tekemiseen.<\/p>\n<p>Kaiken kaikkiaan Machine Learning on tehokas ty\u00f6kalu, jolla on potentiaalia mullistaa tapamme el\u00e4\u00e4 ja ty\u00f6skennell\u00e4. Kun tuotetun tiedon m\u00e4\u00e4r\u00e4 kasvaa jatkuvasti, Machine Learning:n merkitys sen potentiaalin hy\u00f6dynt\u00e4misess\u00e4 vain kasvaa.<\/p>","protected":false},"excerpt":{"rendered":"<p>Tutustu Machine Learning:n tehoon - teko\u00e4lyn osa-alueeseen, jonka avulla tietokonej\u00e4rjestelm\u00e4t oppivat ja kehittyv\u00e4t kokemuksen perusteella ilman nimenomaista ohjelmointia.<\/p>","protected":false},"template":"","meta":{"_acf_changed":false,"inline_featured_image":false,"footnotes":""},"class_list":["post-6620","dictionary","type-dictionary","status-publish","hentry"],"acf":[],"yoast_head":"<!-- This site is optimized with the Yoast SEO Premium plugin v27.3 (Yoast SEO v27.3) - https:\/\/yoast.com\/product\/yoast-seo-premium-wordpress\/ -->\n<title>Machine Learning - The Codest<\/title>\n<meta name=\"description\" content=\"Discover the power of Machine Learning - a subfield of AI that enables computer systems to learn and improve from experience without explicit programming.\" \/>\n<meta name=\"robots\" content=\"index, follow, max-snippet:-1, max-image-preview:large, max-video-preview:-1\" \/>\n<link rel=\"canonical\" href=\"https:\/\/thecodest.co\/fi\/sanakirja\/koneoppiminen\/\" \/>\n<meta property=\"og:locale\" content=\"fi_FI\" \/>\n<meta property=\"og:type\" content=\"article\" \/>\n<meta property=\"og:title\" content=\"Machine Learning\" \/>\n<meta property=\"og:description\" content=\"Discover the power of Machine Learning - 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