{"id":56370,"date":"2020-02-11T00:00:00","date_gmt":"2020-02-10T21:00:00","guid":{"rendered":"https:\/\/prohoster.info\/blog\/blog_prohoster\/kak-energetik-izuchal-nejroseti-i-obzor-na-besplatnyj-kurs-udacity-intro-to-tensorflow-for-deep-learning"},"modified":"2020-02-18T14:04:38","modified_gmt":"2020-02-18T11:04:38","slug":"kak-energetik-izuchal-nejroseti-i-obzor-na-besplatnyj-kurs-udacity-intro-to-tensorflow-for-deep-learning","status":"publish","type":"post","link":"https:\/\/prohoster.info\/sq\/blog\/news\/kak-energetik-izuchal-nejroseti-i-obzor-na-besplatnyj-kurs-udacity-intro-to-tensorflow-for-deep-learning","title":{"rendered":"Si nj\u00eb energjetik, studova rrjetet nervore dhe shqyrtova kursin e lir\u00eb \"Udacity: Intro to TensorFlow for Deep Learning\"","gt_translate_keys":[{"key":"rendered","format":"text"}]},"content":{"rendered":"<p>N\u00eb t\u00eb gjith\u00eb jet\u00ebn time t\u00eb vet\u00ebdijes, kam qen\u00eb energjetik (jo, nuk po flas p\u00ebr ndonj\u00eb pije me vetit\u00eb t\u00eb dyshimta). <\/p>\n<p>Kurr\u00eb nuk kam pasur shum\u00eb interes p\u00ebr bot\u00ebn e teknologjive informative, madje edhe matrica v\u00ebshtir\u00eb se do t\u2019i shum\u00ebzoja n\u00eb nj\u00eb cop\u00eb letre. Dhe kurr\u00eb nuk m\u00eb ka nevojitur kjo, q\u00eb t\u00eb kuptoni pak rreth veprimtaris\u00eb sime, mund t\u00eb ndaj nj\u00eb histori t\u00eb mrekullueshme. Nj\u00eb her\u00eb, k\u00ebrkova nga koleg\u00ebt e mi q\u00eb t\u00eb b\u00ebnin nj\u00eb pun\u00eb n\u00eb Excel \u2013 nj\u00eb tabel\u00eb, kaloi gjysma e dit\u00ebs s\u00eb pun\u00ebs, e afrohem te ata, dhe ata ishin ulur duke sumuar t\u00eb dh\u00ebnat me nj\u00eb kalkulator, po, po, me nj\u00eb kalkulator t\u00eb zakonsh\u00ebm t\u00eb zi me butona. Pra, cila mund t\u00eb jet\u00eb biseda p\u00ebr rrjetet nervore pas k\u00ebsaj?.. Prandaj, kurr\u00eb nuk kam pasur ndonj\u00eb parashikim p\u00ebr t\u00eb hyr\u00eb n\u00eb bot\u00ebn e IT-s\u00eb. Por, si\u00e7 thon\u00eb, \"mir\u00eb \u00ebsht\u00eb aty ku ne nuk jemi\", miqt\u00eb e mi m\u00eb shqet\u00ebsuan me fjal\u00ebt p\u00ebr realitetin e shtuar, p\u00ebr rrjetet nervore, p\u00ebr gjuh\u00ebt e programimit (shum\u00eb kryesisht p\u00ebr Python-in).<\/p>\n<p>Me fjal\u00eb dukej shum\u00eb e thjesht\u00eb, dhe vendosa se p\u00ebrse t\u00eb mos e zot\u00ebroja k\u00ebt\u00eb art magjik, p\u00ebr ta aplikuar n\u00eb fush\u00ebn time t\u00eb aktivitetit.<\/p>\n<p>N\u00eb k\u00ebt\u00eb artikull do ta kaloj p\u00ebrpjekjen time p\u00ebr t\u00eb zot\u00ebruar bazat e Python-it dhe do t\u00eb ndaj me ju p\u00ebrshtypjen time nga kursi falas p\u00ebr TensorFlow nga Udacity.<\/p>\n<p><img decoding=\"async\" alt=\"Si nj\u00eb energjetik, studova rrjetet nervore dhe shqyrtova kursin e lir\u00eb &quot;Udacity: Intro to TensorFlow for Deep Learning&quot;\" src=\"\/wp-content\/uploads\/2020\/02\/d8955ee8fd84fe551521a7675f425073.jpg\" style=\"display:block;margin: 0 auto;\" \/><br \/>\n<noindex><a rel=\"nofollow\" name=\"habracut\"><\/a><\/noindex><\/p>\n<h2> Hyrje<\/h2>\n<p>\nN\u00eb fillim duhet t\u00eb theksoj se pas 11 vjet\u00ebsh n\u00eb energjetik\u00eb, kur ti e di dhe mund t\u00eb b\u00ebsh gjith\u00e7ka dhe madje pak m\u00eb shum\u00eb (sip\u00ebr obligimeve t\u00eb tua), t\u00eb m\u00ebsosh gj\u00ebra krejt\u00ebsisht t\u00eb reja \u2013 n\u00eb nj\u00ebr\u00ebn an\u00eb shkakton nj\u00eb entuziaz\u00ebm t\u00eb fuqish\u00ebm, por n\u00eb an\u00ebn tjet\u00ebr p\u00ebrkthehet n\u00eb dhimbje fizike \"nd\u00ebrsaore n\u00eb kok\u00eb\".<\/p>\n<p>Ende nuk e kam kuptuar plot\u00ebsisht t\u00eb gjitha konceptet baz\u00eb t\u00eb programimit dhe t\u00eb m\u00ebsimit t\u00eb makinerive, prandaj nuk duhet t\u00eb m\u00eb gjykoni rrept\u00ebsisht. Shpresoj q\u00eb artikulli im do t\u00eb jet\u00eb interesant dhe i dobish\u00ebm p\u00ebr njer\u00ebzit si un\u00eb, t\u00eb larg\u00ebt nga zhvillimi i softuerit.<\/p>\n<p>Para se t\u00eb kaloj n\u00eb p\u00ebrmbledhjen e kursit, do t\u00eb them se p\u00ebr studimin e tij do t\u00eb k\u00ebrkohet t\u00eb pakt\u00ebn nj\u00eb njohuri minimale e Python-it. Mund t\u00eb lexoni disa libra p\u00ebr fillestar\u00ebt (un\u00eb kam filluar gjithashtu nj\u00eb kurs n\u00eb Stepic, por ende nuk e kam p\u00ebrfunduar). <\/p>\n<p>N\u00eb kursin p\u00ebr TensorFlow nuk do t\u00eb ket\u00eb konstrukcione t\u00eb komplikuara, por do t\u00eb jet\u00eb e nevojshme t\u00eb kuptoni se p\u00ebrse importohen bibliotekat, si p\u00ebrcaktohet nj\u00eb funksion dhe pse di\u00e7ka p\u00ebrfshihet n\u00eb t\u00eb.<\/p>\n<h2> Pse TensorFlow dhe Udacity? <\/h2>\n<p>\nQ\u00ebllimi kryesor i studimit tim ishte d\u00ebshira p\u00ebr t\u00eb njohur fotografit\u00eb e elementeve t\u00eb instalimeteve elektrike p\u00ebrmes rrjet\u00ebve neurale. <\/p>\n<p>TensorFlow e zgjodha sepse d\u00ebgjoja p\u00ebr t\u00eb nga shok\u00ebt e mi. Dhe si\u00e7 e kuptova, ky kurs \u00ebsht\u00eb mjaft i njohur.<\/p>\n<p>P\u00ebrpiqesha t\u00eb filloja studimin me t\u00eb <noindex><a rel=\"nofollow\" href=\"https:\/\/www.tensorflow.org\/tutorials\"> tutorialin <\/a><\/noindex>.<\/p>\n<p>Dhe menj\u00ebher\u00eb u ndesha me dy probleme.<\/p>\n<ul>\n<li>Materialet edukative ishin t\u00eb shumta dhe shkonin n\u00eb kaos. T\u00eb formoja edhe nj\u00eb pamje mjaft t\u00eb qart\u00eb p\u00ebr zgjidhjen e problemit t\u00eb njohjes s\u00eb imazheve, ishte shum\u00eb e v\u00ebshtir\u00eb p\u00ebr mua. <\/li>\n<li>Shumica e artikujve q\u00eb m\u00eb duhen nuk jan\u00eb p\u00ebrkthyer n\u00eb rusisht. K\u00ebshtu ndodhi q\u00eb n\u00eb f\u00ebmij\u00ebri m\u00ebsova gjermanisht dhe tani, si shum\u00eb f\u00ebmij\u00eb t\u00eb ish-Bashkimit Sovjetik, nuk e di as gjermanishten, as anglezen. Sigurisht, gjat\u00eb jet\u00ebs time t\u00eb vet\u00ebdijshme, kam p\u00ebrpiqur t\u00eb zot\u00ebroj anglishten, por e kam arritur m\u00eb shum\u00eb si n\u00eb figur\u00eb. <\/li>\n<\/ul>\n<p>\n<img decoding=\"async\" alt=\"Si nj\u00eb energjetik, studova rrjetet nervore dhe shqyrtova kursin e lir\u00eb &quot;Udacity: Intro to TensorFlow for Deep Learning&quot;\" src=\"\/wp-content\/uploads\/2020\/02\/44250d475745cf02ee7126e31f695c3b.jpg\" style=\"display:block;margin: 0 auto;\" \/><br \/>\n<br \/>\nPas nj\u00eb k\u00ebrkimi n\u00eb faqen zyrtare, gjeta rekomandime p\u00ebr t\u00eb ndjekur <noindex><a rel=\"nofollow\" href=\"https:\/\/www.tensorflow.org\/resources\/learn-ml\/basics-of-machine-learning\/\"> nj\u00eb nga dy kursit on-line<\/a><\/noindex>.<\/p>\n<p>Si\u00e7 e kuptova, kursi n\u00eb Coursera ishte me pages\u00eb, nd\u00ebrsa kursi <noindex><a rel=\"nofollow\" href=\"https:\/\/www.udacity.com\/course\/intro-to-tensorflow-for-deep-learning--ud187\"> Udacity: Intro to TensorFlow for Deep Learning<\/a><\/noindex> mund t\u00eb ndiqet \"pa pages\u00eb, dmth falas.\"<\/p>\n<h2> P\u00ebrmbajtja e kursit<\/h2>\n<p>\nKursi p\u00ebrb\u00ebn 9 m\u00ebsime. <\/p>\n<p>Seksyoni i par\u00eb \u00ebsht\u00eb hyr\u00ebs, aty do t\u00eb flasin p\u00ebr arsyen se p\u00ebrse ai \u00ebsht\u00eb n\u00eb thelb i nevojsh\u00ebm.<\/p>\n<p>M\u00ebsimi \u2116 2 doli t\u00eb ishte m\u00ebsimi im i preferuar. Ai ishte mjaft i thjesht\u00eb p\u00ebr t'u kuptuar dhe gjithashtu demonstroi mrekullit\u00eb e shkenc\u00ebs. N\u00eb thelb, n\u00eb k\u00ebt\u00eb m\u00ebsim p\u00ebrve\u00e7 informacionit baz\u00eb p\u00ebr rrjetet neurale, krijuesit demonstrojn\u00eb se si me ndihm\u00ebn e nj\u00eb rrjeti neural me nj\u00eb shtres\u00eb mund t\u00eb zgjidhet problemi i konvertimit t\u00eb temperatur\u00ebs nga grad\u00ebt Fahrenheit n\u00eb grad\u00ebt Celsius.<\/p>\n<p>Ky \u00ebsht\u00eb nj\u00eb shembull n\u00eb t\u00eb v\u00ebrtet\u00eb shum\u00eb ilustrues. Ende po mendoj se si t\u00eb shpik dhe t\u00eb zgjidh nj\u00eb detyr\u00eb t\u00eb ngjashme, por vet\u00ebm p\u00ebr elektricitetin.<\/p>\n<p>Fatkeq\u00ebsisht, m\u00eb pas kam ngecur, sepse t\u00eb m\u00ebsosh gj\u00ebra t\u00eb panjohura n\u00eb nj\u00eb gjuh\u00eb t\u00eb panjohur \u00ebsht\u00eb mjaft e v\u00ebshtir\u00eb. M\u00eb shp\u00ebtoi fakti q\u00eb gjeta n\u00eb Habr <noindex><a rel=\"nofollow\" href=\"https:\/\/habr.com\/ru\/post\/453482\/\">p\u00ebrkthimin e k\u00ebtij kursi n\u00eb gjuh\u00ebn ruse.<\/a><\/noindex>.<\/p>\n<p>P\u00ebrkthimi u krye me cil\u00ebsi, notebook-et Colab gjithashtu jan\u00eb p\u00ebrkthyer, k\u00ebshtu q\u00eb m\u00eb pas shikoja edhe n\u00eb origjinal, edhe n\u00eb p\u00ebrkthim.<\/p>\n<p>M\u00ebsimi \u21163 \u2013 \u00ebsht\u00eb, n\u00eb thelb, nj\u00eb riprodhim i materialeve t\u00eb tutorialit zyrtar t\u00eb TensorFlow. N\u00eb k\u00ebt\u00eb m\u00ebsim m\u00ebsojm\u00eb t\u00eb klasifikojm\u00eb imazhe t\u00eb veshjeve me ndihm\u00ebn e nj\u00eb rrjeti neural me shum\u00eb shtresa (grupi i t\u00eb dh\u00ebnave Fashion MNIST).<\/p>\n<p>Lezionet nga \u21164 n\u00eb \u21167 jan\u00eb gjithashtu nj\u00eb p\u00ebrshtatje e nj\u00eb tutoriali. Por p\u00ebr shkak se ato jan\u00eb nd\u00ebrtuar n\u00eb m\u00ebnyr\u00eb t\u00eb arsyeshme, nuk ka nevoj\u00eb t\u00eb merremi me sekuenc\u00ebn e studimit. N\u00eb k\u00ebto lezione do t\u00eb na tregojn\u00eb shkurtimisht p\u00ebr rrjetet nervore super t\u00eb sakta, p\u00ebr m\u00ebnyr\u00ebn e rritjes s\u00eb sakt\u00ebsis\u00eb s\u00eb m\u00ebsimit dhe ruajtjes s\u00eb modelit. Gjat\u00eb k\u00ebsaj do t\u00eb zgjidhim p\u00ebrfundimisht problemin e klasifikimit t\u00eb qenve dhe maceve n\u00eb nj\u00eb imazh.<\/p>\n<p>Leksioni \u21168 p\u00ebrb\u00ebn nj\u00eb kurs krejt\u00ebsisht t\u00eb ve\u00e7ant\u00eb, ka nj\u00eb m\u00ebsues tjet\u00ebr dhe vet\u00eb course \u00ebsht\u00eb mjaft voluminoz. Leksioni i kushtohet serive temporale. Duke qen\u00eb se kjo p\u00ebr momentin nuk m\u00eb intereson, e kam p\u00ebrshkuar me shpejt\u00ebsi.<\/p>\n<p>E p\u00ebrfundon t\u00eb gjith\u00eb leksioni \u21169, i cili \u00ebsht\u00eb nj\u00eb ftes\u00eb p\u00ebr t\u00eb ndjekur nj\u00eb kurs falas mbi TensorFlow lite.<\/p>\n<h2> \u00c7far\u00eb m\u00eb ka p\u00eblqyer dhe \u00e7far\u00eb nuk m\u00eb ka p\u00eblqyer<\/h2>\n<p>\nLe t\u00eb fillojm\u00eb me p\u00ebrfitimet:<\/p>\n<ul>\n<li> Kursi \u00ebsht\u00eb falas <\/li>\n<li> Kursi \u00ebsht\u00eb p\u00ebr TensorFlow 2. Disa libra q\u00eb kam par\u00eb dhe disa kurse n\u00eb internet qen\u00eb p\u00ebr TensorFlow 1. Nuk e di n\u00ebse ka ndonj\u00eb ndryshim t\u00eb madh, por \u00ebsht\u00eb k\u00ebnaq\u00ebsi t\u00eb m\u00ebsoj versionin aktual. <\/li>\n<li> M\u00ebsuesit n\u00eb video nuk irritojn\u00eb (edhe pse n\u00eb versionin rus lexojn\u00eb jo aq energjikisht si n\u00eb origjinal) <\/li>\n<li> Kursi nuk k\u00ebrkon shum\u00eb koh\u00eb<\/li>\n<li> Kursi nuk t\u00eb fut n\u00eb ndjenja d\u00ebshp\u00ebrimi dhe pafund\u00ebsie. Detyrat n\u00eb kurs jan\u00eb t\u00eb thjeshta dhe gjithmon\u00eb ka nj\u00eb ndihm\u00eb n\u00eb form\u00ebn e Colab me zgjidhjen e sakt\u00eb, n\u00ebse di\u00e7ka nuk kuptohet (ndihesh, se nj\u00eb gjysm\u00eb e mir\u00eb e detyrave nuk m\u00eb ishte e qart\u00eb) <\/li>\n<li> Nuk \u00ebsht\u00eb nevoja t\u00eb instalosh asgj\u00eb, t\u00eb gjitha laborator\u00ebt e kursit mund t\u00eb b\u00ebhen n\u00eb shfletues<\/li>\n<\/ul>\n<p>\nTani p\u00ebr disavantazhet:<\/p>\n<ul>\n<li> Nj\u00eb num\u00ebr praktikisht asnj\u00eb material kontrolli. As teste, as detyra, asgj\u00eb p\u00ebr t\u00eb verifikuar p\u00ebrvet\u00ebsimin e kursit <\/li>\n<li> Jo t\u00eb gjith\u00eb notebook\u00ebt e mi funksionuan si\u00e7 duhet. M\u00eb duket, n\u00eb leksionin e tret\u00eb t\u00eb kursit origjinal n\u00eb anglisht, Colab nxori nj\u00eb gabim dhe nuk dija \u00e7far\u00eb t\u00eb b\u00ebja me t\u00eb <\/li>\n<li> \u00cbsht\u00eb e p\u00ebrshtatshme t\u00eb shikohet vet\u00ebm n\u00eb kompjuter. Ndoshta nuk kam kuptuar plot\u00ebsisht, por nuk e gjej aplikacionin Udacity n\u00eb telefonin tim t\u00eb men\u00e7ur. Dhe versioni celular i sitit nuk \u00ebsht\u00eb adaptiv, dometh\u00ebn\u00eb, thuajse i gjith\u00eb ekrani z\u00eb menuja e navigimit, por p\u00ebr t\u00eb par\u00eb p\u00ebrmbajtjen kryesore duhet t\u00eb l\u00ebviz\u00ebsh djathtas p\u00ebrtej fush\u00ebs s\u00eb pamjes. Po ashtu, video nuk mund t\u00eb shikohet n\u00eb telefon. N\u00eb nj\u00eb ekran prej rreth 6 in\u00e7esh nuk shikohet asgj\u00eb mir\u00eb.<\/li>\n<li>Disa disa n\u00eb kurs rishikohen disa her\u00eb, por nuk shpjegohen n\u00eb t\u00eb v\u00ebrtet\u00eb gj\u00ebrat q\u00eb jan\u00eb me t\u00eb v\u00ebrtet\u00eb t\u00eb nevojshme p\u00ebr rrjetet konvolucione. Nuk e kuptova q\u00ebllimin global t\u00eb disa ushtrimeve (p.sh., p\u00ebrse \u00ebsht\u00eb e nevojshme Max Pooling). <\/li>\n<\/ul>\n<p><\/p>\n<h2> CV<\/h2>\n<p>\nSigurisht, ju tashm\u00eb e keni kuptuar se nuk ndodhi ndonj\u00eb mrekulli. Dhe pas kalimit t\u00eb k\u00ebtij kursi t\u00eb shkurt\u00ebr, nuk \u00ebsht\u00eb e mundur t\u00eb kuptoni me t\u00eb v\u00ebrtet\u00eb se si funksionojn\u00eb rrjetet nervore.<\/p>\n<p>Natyrisht, pas k\u00ebsaj nuk arrita t\u00eb zgjidh problemin tim me klasifikimin e fotografive t\u00eb nd\u00ebrprer\u00ebsve dhe butonave n\u00eb pajisjet shp\u00ebrndar\u00ebse. <\/p>\n<p>Por, n\u00eb p\u00ebrgjith\u00ebsi, kursi \u00ebsht\u00eb i dobish\u00ebm. Ai tregon se \u00e7far\u00eb mund t\u00eb b\u00ebhet me TensorFlow dhe n\u00eb cilin drejtim duhet t\u00eb l\u00ebvizni m\u00eb tej. <\/p>\n<p>Mendoj se p\u00ebr fillim duhet t\u00eb m\u00ebsoj bazat e Python dhe t\u00eb lexoj libra n\u00eb gjuh\u00ebn shqipe rreth m\u00ebnyr\u00ebs si funksionojn\u00eb rrjetet nervore, e pastaj t\u00eb merrem me TensorFlow.<\/p>\n<p>N\u00eb p\u00ebrfundim, do t\u00eb doja t\u00eb falenderoja miqt\u00eb e mi p\u00ebr shtytjen q\u00eb m\u00eb dhan\u00eb p\u00ebr t\u00eb shkruar artikullin tim t\u00eb par\u00eb n\u00eb 'Habr' dhe p\u00ebr ndihm\u00ebn n\u00eb formatimin e tij.<\/p>\n<p>P.S. Do t\u00eb isha i lumtur p\u00ebr komentet tuaja dhe \u00e7do kritik\u00eb konstruktive.<br \/>\n<br \/>Burimi: <a content=\"nofollow\" rel=\"nofollow\" href=\"https:\/\/habr.com\/ru\/post\/487950\/\">habr.com<\/a><\/p>","protected":false,"gt_translate_keys":[{"key":"rendered","format":"html"}]},"excerpt":{"rendered":"<p>\u0412\u0441\u044e \u0441\u0432\u043e\u044e \u0441\u043e\u0437\u043d\u0430\u0442\u0435\u043b\u044c\u043d\u0443\u044e \u0436\u0438\u0437\u043d\u044c, \u044f \u0431\u044b\u043b \u044d\u043d\u0435\u0440\u0433\u0435\u0442\u0438\u043a\u043e\u043c (\u043d\u0435\u0442, \u0441\u0435\u0439\u0447\u0430\u0441 \u0440\u0435\u0447\u044c \u043d\u0435 \u0438\u0434\u0435\u0442 \u043e \u043d\u0430\u043f\u0438\u0442\u043a\u0435 \u0441 \u0441\u043e\u043c\u043d\u0438\u0442\u0435\u043b\u044c\u043d\u044b\u043c\u0438 \u0441\u0432\u043e\u0439\u0441\u0442\u0432\u0430\u043c\u0438). \u042f \u043d\u0438\u043a\u043e\u0433\u0434\u0430 \u043e\u0441\u043e\u0431\u043e \u043d\u0435 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\u043c\u043e\u0433\u0443 \u043f\u043e\u0434\u0435\u043b\u0438\u0442\u044c\u0441\u044f \u0437\u0430\u043c\u0435\u0447\u0430\u0442\u0435\u043b\u044c\u043d\u043e\u0439 [&hellip;]<\/p>\n","protected":false,"gt_translate_keys":[{"key":"rendered","format":"html"}]},"author":1,"featured_media":0,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[702],"tags":[],"class_list":["post-56370","post","type-post","status-publish","format-standard","hentry","category-news"],"aioseo_notices":[],"aioseo_head":"\n\t\t<!-- All in One SEO 5.0.2 - aioseo.com -->\n\t<meta name=\"description\" content=\"\u0412\u0441\u044e \u0441\u0432\u043e\u044e \u0441\u043e\u0437\u043d\u0430\u0442\u0435\u043b\u044c\u043d\u0443\u044e \u0436\u0438\u0437\u043d\u044c, \u044f \u0431\u044b\u043b \u044d\u043d\u0435\u0440\u0433\u0435\u0442\u0438\u043a\u043e\u043c (\u043d\u0435\u0442, \u0441\u0435\u0439\u0447\u0430\u0441 \u0440\u0435\u0447\u044c 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