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[{"key": "dc.contributor.advisor", "value": "Hakanen, Jussi", "language": "", "element": "contributor", "qualifier": "advisor", "schema": "dc"}, {"key": "dc.contributor.advisor", "value": "Ojalehto, Vesa", "language": "", "element": "contributor", "qualifier": "advisor", "schema": "dc"}, {"key": "dc.contributor.author", "value": "Kurkinen, Jani", "language": "", "element": "contributor", "qualifier": "author", "schema": "dc"}, {"key": "dc.date.accessioned", "value": "2019-08-02T07:14:12Z", "language": null, "element": "date", "qualifier": "accessioned", "schema": "dc"}, {"key": "dc.date.available", "value": "2019-08-02T07:14:12Z", "language": null, "element": "date", "qualifier": "available", "schema": "dc"}, {"key": "dc.date.issued", "value": "2019", "language": "", "element": "date", "qualifier": "issued", "schema": "dc"}, {"key": "dc.identifier.uri", "value": "https://jyx.jyu.fi/handle/123456789/65188", "language": null, "element": "identifier", "qualifier": "uri", "schema": "dc"}, {"key": "dc.description.abstract", "value": "Tutkielmassa tarkastellaan, mink\u00e4laisia vaiheita tyypillinen syv\u00e4oppimista hy\u00f6dynt\u00e4v\u00e4 projekti sis\u00e4lt\u00e4\u00e4 ja mink\u00e4laisilla ty\u00f6kaluilla se voidaan toteuttaa. Tarkoituksena on selvitt\u00e4\u00e4, miten tietyill\u00e4 ohjelmistoty\u00f6kaluilla saadaan tuloksia aikaan valmiiksi ker\u00e4tyll\u00e4 datalla. Lis\u00e4ksi kerrotaan lyhyesti syv\u00e4oppimiseen liittyv\u00e4st\u00e4 teoriasta ja demonstroidaan, miten valituilla ty\u00f6kaluilla voidaan rakentaa ja kouluttaa neuroverkko sek\u00e4 k\u00e4ytt\u00e4\u00e4 sit\u00e4 kuvantunnistukseen. Kuvantunnistusta voi tehd\u00e4 useilla eri ty\u00f6kaluilla, ja t\u00e4h\u00e4n tutkielmaan valitut ty\u00f6kalut osoittautuivat hyviksi vaihtoehdoiksi helppok\u00e4ytt\u00f6isyytens\u00e4 ja monipuolisuutensa ansioista.", "language": "fi", "element": "description", "qualifier": "abstract", "schema": "dc"}, {"key": "dc.description.abstract", "value": "This thesis describes what phases a typical deep learning project has and what tools can be used to implement it. The aim is to explore how to get results with certain software tools with existing data. In addition, theory behind deep learning will be briefly introduced. The practical part of this thesis demonstrates how a neural network can be built, trained and used for image classification with selected tools. Image classification can be done with various tools and the ones used in this thesis proved to be good choices because of their ease of use and feature richness.", "language": "en", "element": "description", "qualifier": "abstract", "schema": "dc"}, {"key": "dc.description.provenance", "value": "Submitted by Paivi Vuorio (paelvuor@jyu.fi) on 2019-08-02T07:14:12Z\nNo. of bitstreams: 0", "language": "en", "element": "description", "qualifier": "provenance", "schema": "dc"}, {"key": "dc.description.provenance", "value": "Made available in DSpace on 2019-08-02T07:14:12Z (GMT). No. of bitstreams: 0\n Previous issue date: 2019", "language": "en", "element": "description", "qualifier": "provenance", "schema": "dc"}, {"key": "dc.format.extent", "value": "60", "language": "", "element": "format", "qualifier": "extent", "schema": "dc"}, {"key": "dc.format.mimetype", "value": "application/pdf", "language": null, "element": "format", "qualifier": "mimetype", "schema": "dc"}, {"key": "dc.language.iso", "value": "eng", "language": null, "element": "language", "qualifier": "iso", "schema": "dc"}, {"key": "dc.rights", "value": "In Copyright", "language": "en", "element": "rights", "qualifier": null, "schema": "dc"}, {"key": "dc.title", "value": "On practicalities of identifying and implementing a suitable software architecture for a typical deep learning data science project", "language": "", "element": "title", "qualifier": null, "schema": "dc"}, {"key": "dc.type", "value": "master thesis", "language": null, "element": "type", "qualifier": null, "schema": "dc"}, 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