{"id":2124,"date":"2018-09-29T05:42:26","date_gmt":"2018-09-29T05:42:26","guid":{"rendered":"http:\/\/sadievrenseker.com\/wp\/?p=2124"},"modified":"2018-11-24T15:06:37","modified_gmt":"2018-11-24T15:06:37","slug":"ian-502-veri-odakli-programlama-2018","status":"publish","type":"post","link":"https:\/\/sadievrenseker.com\/?p=2124","title":{"rendered":"IAN 502 Veri Odakl\u0131 Programlama 2018"},"content":{"rendered":"<p style=\"text-align: center;\">T. C. \u0130stanbul \u015eehir \u00dcniversitesi<\/p>\n<p style=\"text-align: center;\">\u0130\u015f Analiti\u011fi Y\u00fcksek Lisans Dersi<\/p>\n<p style=\"text-align: center;\">Ders izlencesi ve ders ile ilgili faydal\u0131 i\u00e7erik<\/p>\n<p><strong>Dersin Ad\u0131<\/strong>: Veri Odakl\u0131 Programlama, Python ile<\/p>\n<p><strong>Dersin Kodu:<\/strong> IAN 502<\/p>\n<p><strong>D\u00f6nemi:<\/strong> G\u00fcz 2018<\/p>\n<p><strong>Kredisi :<\/strong> 3<\/p>\n<p><strong>\u00d6\u011fretim \u00dcyesi:<\/strong> Do\u00e7. Dr. \u015eadi Evren \u015eEKER<\/p>\n<p><strong>\u0130leti\u015fim:<\/strong> python2018@sadievrenseker.com<\/p>\n<p><strong>Ders \u0130\u00e7eri\u011fi:<\/strong><br \/>\nVeri odakl\u0131 programlama dersinin 3 farkl\u0131 seviyeden \u00f6\u011frencilere hitap etmesi beklenmektedir. Hen\u00fcz programlama ile yeni tan\u0131\u015fan ki\u015filer, programlama hakk\u0131nda bilgisi olan ama \u00e7ok fazla tecr\u00fcbesi ve uzmanl\u0131\u011f\u0131 olmayan ki\u015filer ve progralama konusunda tecr\u00fcbeli ve uzman ancak veri odakl\u0131 progralmama konusuna yeni olan kat\u0131l\u0131mc\u0131lar.<\/p>\n<p>Dersin amac\u0131, programlama bilgisi olmayan ki\u015filerin programlama dilleri ile ilk kez kar\u015f\u0131la\u015faca\u011f\u0131 ve kodlaman\u0131n temellerini \u00f6\u011frenece\u011fi ve sonras\u0131nda veri odakl\u0131 program yazabilece\u011fi ge\u00e7i\u015fi sa\u011flamakt\u0131r.<\/p>\n<p>Programlama ge\u00e7mi\u015fi olan ki\u015filere ise daha \u00e7ok veri temelli program yazabilecekleri, veri analizinde kar\u015f\u0131la\u015facaklar\u0131 problemlere kar\u015f\u0131l\u0131k gelen u\u00e7tan uca problem \u00e7\u00f6z\u00fcmlerini geli\u015ftirebilecekleri programlama yeteneklerini \u00f6\u011fretmektir.<\/p>\n<p>Ders kapsam\u0131nda <strong>Python<\/strong> programlama dili \u00f6\u011fretilecek olup, dilin temellerinin yan\u0131nda veri analizine y\u00f6nelik olarak, python dili i\u00e7erisinde bulunan baz\u0131 k\u00fct\u00fcphaneler a\u015fa\u011f\u0131daki \u015fekildedir:<\/p>\n<ul>\n<li>\u00b7\u00a0\u00a0\u00a0\u00a0\u00a0 NumPy<\/li>\n<li>\u00b7\u00a0\u00a0\u00a0\u00a0\u00a0 SciPy<\/li>\n<li>\u00b7\u00a0\u00a0\u00a0\u00a0\u00a0 Pandas<\/li>\n<li>\u00b7\u00a0\u00a0\u00a0\u00a0\u00a0 Matplotlib<\/li>\n<li>\u00b7\u00a0\u00a0\u00a0\u00a0\u00a0 Scikit-learn<\/li>\n<\/ul>\n<p>Ayr\u0131ca g\u00fcncel konulara da yer verilecek ve \u00f6rne\u011fin derin \u00f6\u011frenme gibi konular i\u00e7in de tensor flow benzeri k\u00fct\u00fcphanelere giri\u015f yap\u0131lacakt\u0131r.<\/p>\n<p>Dersin amac\u0131, kat\u0131l\u0131mc\u0131lar\u0131, veri bilimi, veri analiti\u011fi ve i\u015f analiti\u011fi d\u00fcnyas\u0131nda kullan\u0131lan temel teknolojileri, algoritmalar\u0131 ve g\u00f6rselle\u015ftirme \/ analiz ara\u00e7lar\u0131n\u0131 temel d\u00fczeyde kullanacak seviyeye getirmektir.<\/p>\n<p><strong>Kaynak Kitaplar<\/strong><\/p>\n<ul>\n<li>Python for Data Analysis, 2nd Edition\u00a0Data Wrangling with Pandas, NumPy, and IPython, \u00a0William McKinney, 2017<\/li>\n<li>Learning scikit-learn: Machine Learning in Python\u00a0Paperback\u00a0\u2013 November 25, 2013, Ra\u00fal Garreta, Guillermo Moncecchi<\/li>\n<li>Building Machine Learning Systems with Python\u00a0, Willi Richert, Luis Pedro Coelho\u00a0, 2013<\/li>\n<\/ul>\n<p><strong>Online Kaynaklar<\/strong><\/p>\n<ul>\n<li><a href=\"https:\/\/www.udemy.com\/makine-ogrenmesi\/\">Udemy &#8211; Makine \u00d6\u011frenmesi<\/a><\/li>\n<\/ul>\n<p>Ders boyunca \u00f6\u011frencilere okumalar\u0131 gereken baz\u0131 ufak vaka \u00e7al\u0131\u015fmalar\u0131 ile makaleler verilecektir.<\/p>\n<p><strong>Derse Kat\u0131l\u0131m:<\/strong><\/p>\n<p>Ders boyunca \u00f6\u011frencilere okumalar\u0131 gereken baz\u0131 ufak vaka \u00e7al\u0131\u015fmalar\u0131 ile makaleler verilecektir.<\/p>\n<p><strong>Derse Kat\u0131l\u0131m:<\/strong><br \/>\nDers 3 mod\u00fclden olu\u015fmaktad\u0131r.<br \/>\n1. Programlamaya giri\u015f (hi\u00e7 bilmeyenler i\u00e7in)<br \/>\n2. Makine \u00f6\u011frenmesi ve veri analiti\u011fine giri\u015f<br \/>\n3. \u0130leri veri analiti\u011fi y\u00f6ntemleri<br \/>\nKat\u0131l\u0131mc\u0131lar, farkl\u0131 bilgi d\u00fczeylerinden geldikleri i\u00e7in ilk mod\u00fcle kat\u0131l\u0131m zorunlu olmamakla birlikte verilen b\u00fct\u00fcn \u00f6dev ve projelerin yap\u0131lmas\u0131 zorunludur. Sadece 3 hafta s\u00fcrecek, ilk mod\u00fcl i\u00e7in benimle g\u00f6r\u00fc\u015ferek \u00f6ncesinde izin alabilir ve \u00f6dev\/projeleri yaparak ilk mod\u00fclden muaf say\u0131labilirler. Bunun d\u0131\u015f\u0131nda, derse kat\u0131l\u0131m zorunlu olup, \u00f6zel durumlar i\u00e7in \u00f6nceden haberle\u015filerek izin al\u0131nabilir. Dersleri ka\u00e7\u0131rma veya tekrar \u00e7al\u0131\u015fma ihtimallerine kar\u015f\u0131, ders boyunca dijital i\u00e7erik olu\u015fturularak \u00f6\u011frencilerle azami seviyede payla\u015f\u0131lmaya \u00e7al\u0131\u015f\u0131lacakt\u0131r.<br \/>\n<strong>Derste yap\u0131lacaklar:<\/strong><br \/>\n\u2022 Yap\u0131sal programlamaya (structural programming) giri\u015f : temel programlama teknikleri, de\u011fi\u015fken, d\u00f6ng\u00fc, ko\u015fullar ve fonksiyon gibi temel kavramlara giri\u015f ve uygulamalar\u0131<br \/>\n\u2022 Veri yap\u0131lar\u0131na giri\u015f (Data structures): temel veri yap\u0131lar\u0131n\u0131n \u00e7al\u0131\u015fma mant\u0131\u011f\u0131 ve kullan\u0131m alanlar\u0131, diziler, listeler, y\u0131\u011f\u0131n (stack), s\u0131ra (queue), a\u011fa\u00e7lar (trees) , haritalar (maps), v.b. kavramlar.<br \/>\n\u2022 Nesne Y\u00f6nelimli programlamaya giri\u015f (object oriented programming) : Nesne, kal\u0131t\u0131m (inheritance), kaps\u00fclleme (encapsulation), \u00e7ok \u015fekillilik (polymorphism) v.b. kavramlar.<br \/>\n\u2022 Veri analizine giri\u015f ve veri k\u00fcmelerinin y\u00f6netilmesi \/ y\u00fcklenmesi<br \/>\n\u2022 NumPy temelleri ve temel dizi analizi, vekt\u00f6rize hesaplamalar, dosya i\u015flemleri ve do\u011frusal cebir (linear algebra), rasgele say\u0131 (random number) \u00fcretimi<br \/>\n\u2022 Tan\u0131mlay\u0131c\u0131 istatisti\u011fe giri\u015f (descriptive statistics), Pandas k\u00fct\u00fcphanesi ve veri yap\u0131lar\u0131<br \/>\n\u2022 Dosya y\u00fckleme (Loading) , saklama (Storage) ve dosya formatlar\u0131<br \/>\n\u2022 Veri \u00f6n i\u015fleme ve ver sarmallama (wrangling): veri k\u00fcmelerinin birle\u015ftirilmesi ve eklenmesi, yeniden \u015fekillendirme (reshaping) ve d\u00f6nd\u00fcrme (pivoting), veri d\u00f6n\u00fc\u015f\u00fcm\u00fc (data Transformation), ve dizgi i\u015flemleri (string manipulations)<br \/>\n\u2022 Tahminci istatisti\u011fe giri\u015f (predictive statistics), scikit-learn k\u00fct\u00fcphanesi ve temel s\u0131n\u0131fland\u0131rma, k\u00fcmeleme ve regrezisyon analizi y\u00f6ntemlerinin kullan\u0131lmas\u0131<br \/>\n\u2022 \u00c7izim ve g\u00f6rselle\u015ftirme (plotting and visualization): matplotlib k\u00fct\u00fcphanesine giri\u015f, pandas ile fonksiyonlar\u0131n g\u00f6rselle\u015ftirilmesi, di\u011fer alternatif g\u00f6rselle\u015ftirme ara\u00e7lar\u0131na giri\u015f<br \/>\n\u2022 Grup operasyonlar\u0131 ile veri birle\u015ftirme (data aggregation): GrouBy \u00e7al\u0131\u015fmas\u0131, veri birle\u015ftirme (aggregation), grup boyunca operasyonlar ve d\u00f6n\u00fc\u015f\u00fcmler (transformations), pivot tablolar ve \u00e7apraz tablolama.<br \/>\n\u2022 Zaman Serileri: Tarih ve zaman veri tipleri, zaman serilerine giri\u015f, veri aral\u0131klar\u0131 (Ranges), frekans ve kayma (shift) kavramlar\u0131, Priyotlar ve periyodik aritmetik, hareketli pencere fonksiyonlar\u0131 (moving window functions).<br \/>\n\u2022 G\u00fcncel ve geli\u015fmekte olan veri analizi y\u00f6ntemlerinin python ile kullan\u0131lmas\u0131: ileri makine \u00f6\u011frenmesi k\u00fct\u00fcphaneleri, derin \u00f6\u011frenme k\u00fct\u00fcphaneleri.<br \/>\n<strong>Vaka \u00c7al\u0131\u015fmalar\u0131:<\/strong><br \/>\nDers kapsam\u0131nda, uygulama e\u011fitim yolu izlenecektir ve \u00e7ok say\u0131da vaka \u00fczerinde veri analizi python dili kullan\u0131larak yap\u0131lacakt\u0131r. Ders kapsam\u0131nda verilen \u00f6rnek veri k\u00fcmeleri \u00fczerinde kat\u0131l\u0131mc\u0131lar\u0131 ger\u00e7ek hayat projelerini uygulamalar\u0131 beklenmektedir.<\/p>\n<p><strong>\u00d6devler:<\/strong><br \/>\nDers kapsam\u0131nda, 13 farkl\u0131 \u00f6dev verilmesi planlanmaktad\u0131r. Bu \u00f6devlerin s\u00fcresi bir hafta ile iki hafta aras\u0131nda de\u011fi\u015fmekle birlikte genelde her hafta yeni bir \u00f6dev verilecektir. \u00d6devler grup halinde yap\u0131lacakt\u0131r ve her \u00f6dev i\u00e7in yeni bir grup kurulacak bu sayede grup \u00e7al\u0131\u015fmas\u0131 te\u015fvik edilecektir.<\/p>\n<p><strong>Ders i\u00e7i uygulamalar:<\/strong><br \/>\nDerste anlat\u0131lan konular, kat\u0131l\u0131mc\u0131lar ile birlikte birebir \u00f6rnek veriler \u00fczerinde uygulanacakt\u0131r. Bu y\u00fczden kat\u0131l\u0131mc\u0131la\u0131rn bilgisayarlar\u0131n\u0131 getirmeleri ve ilk derste anlat\u0131lan python yaz\u0131l\u0131m\u0131n\u0131 kurmalar\u0131 gerekmektedir, ayr\u0131ca her ders i\u00e7in gereken ilave k\u00fct\u00fcphaneler bir \u00f6nceki derste veya ilgili derste anlat\u0131lacakt\u0131r.<\/p>\n<p><strong>Ders Web Sitesi<\/strong><br \/>\nDers i\u00e7erikleri ve bu ders izlencesi, www.sadievrenseker.com\/python2017 adresinden takip edilebilir. Verilen \u00f6devler, projeler ve gerekli yaz\u0131l\u0131m i\u00e7in ba\u011flant\u0131lar sayfada g\u00fcncel olarak yer alacakt\u0131r.<\/p>\n<p><strong>Tak\u0131m \u00c7al\u0131\u015fmas\u0131 ve Tak\u0131m \u00dcyesi De\u011ferlendirmesi<\/strong><br \/>\n\u00d6\u011frenciler kendi tak\u0131mlar\u0131n\u0131n her bir \u00fcyesini projedeki performans\u0131na g\u00f6re de\u011ferlendireceklerdir. Her bir \u00f6\u011frenci 100 puan\u0131 kendisi de dahil olacak \u015fekilde tak\u0131m arkada\u015flar\u0131na da\u011f\u0131tacakt\u0131r. Bu da\u011f\u0131t\u0131m \u00f6\u011frencinin her bir tak\u0131m \u00fcyesinin projeye katk\u0131s\u0131n\u0131 yans\u0131tacak \u015fekilde yap\u0131lacakt\u0131r. Puanlama, tak\u0131m \u00fcyesinin projeye harcad\u0131\u011f\u0131 zaman\u0131 de\u011fil, projeye olan katk\u0131s\u0131n\u0131 \u00f6l\u00e7ecek \u015fekilde yap\u0131lmal\u0131d\u0131r. Katk\u0131dan kas\u0131t, fikir geli\u015ftirme, ara\u015ft\u0131rma, analiz, yaz\u0131 yazma, s\u00f6zl\u00fc sunum, rapor yazma vb.\u2019dir. E\u011fer tak\u0131m \u00e7al\u0131\u015fmas\u0131 iyi ise o zaman \u00f6\u011frenciler ayn\u0131 puan\u0131 di\u011fer tak\u0131m \u00fcyelerine verebilirler. Ancak baz\u0131 tak\u0131m \u00fcyeleri kendi yapmalar\u0131 gerekeni yerine getirmediyse bu durumda puanlar e\u015fit olmayan bir \u015fekilde da\u011f\u0131t\u0131lacakt\u0131r.<\/p>\n<p>T\u00fcm tak\u0131m \u00fcyeleri taraf\u0131ndan verilen puanlar ders hocas\u0131 taraf\u0131ndan k\u00fcm\u00fclatif hale getirilecektir. Her bir \u00f6\u011frenci kendi tak\u0131m arkada\u015flar\u0131n\u0131n ve kendisinin verdi\u011fi puana g\u00f6re bir tak\u0131m \u00e7al\u0131\u015fmas\u0131 katk\u0131 puan\u0131 alacak, ama bu puan\u0131n nas\u0131l olu\u015ftu\u011fu (kimin kime ka\u00e7 puan verdi\u011fi bilgisi) \u00f6\u011frenciler ile payla\u015f\u0131lmayacakt\u0131r).<\/p>\n<p>Tak\u0131m \u00fcyeleri aras\u0131nda bir konsens\u00fcs olu\u015fmad\u0131\u011f\u0131 zamanlarda; \u00f6rne\u011fin \u00fc\u00e7 \u00f6\u011frencinin puanlar\u0131 e\u015fit da\u011f\u0131tmas\u0131 ve bir \u00f6\u011frencinin farkl\u0131 puanlama yapmas\u0131 gibi bir durumda, hoca kendi muhakemesini kullanarak tak\u0131m katk\u0131 puan\u0131 hesaplayacakt\u0131r. Bu hesaplama esnas\u0131nda tak\u0131m \u00fcyeleri ile g\u00f6r\u00fc\u015fmesi gerekebilir.<\/p>\n<p>E\u011fer birbiri ile \u00e7eli\u015fen puanlamalar s\u00f6z konusu ise hoca b\u00fcy\u00fck ihtimalle tak\u0131m \u00fcyeleri ile m\u00fclakat yapacak ve ona g\u00f6re puanlama yapacakt\u0131r.<\/p>\n<p>Ge\u00e7mi\u015f tecr\u00fcbeler \u00e7o\u011fu tak\u0131m\u0131n puanlar\u0131n\u0131 e\u015fit olarak da\u011f\u0131tt\u0131klar\u0131 \u015feklindedir. Tak\u0131m \u00e7al\u0131\u015fmas\u0131n\u0131n proje notunu etkiledi\u011fi durumlar az\u0131nl\u0131kta bulunmaktad\u0131r. Bu puanlaman\u0131n amac\u0131 tak\u0131mlar\u0131na destek olmayan tak\u0131m \u00fcyelerinin hak etmedikleri puan\u0131 alman\u0131n \u00f6n\u00fcne ge\u00e7mektir. Ayn\u0131 zamanda, baz\u0131 \u00f6\u011frencilerin pay\u0131ndan \u00e7ok daha fazlas\u0131n\u0131 yapmalar\u0131 durumunda \u00f6\u011frencinin puan\u0131n\u0131n daha da yukar\u0131ya ta\u015f\u0131mak m\u00fcmk\u00fcn olacakt\u0131r.<\/p>\n<p>Tak\u0131m de\u011ferlendirmesinin puanlamas\u0131 sizin proje puan\u0131n\u0131za direkt etki edecektir. \u00d6rne\u011fin, tak\u0131m puan\u0131 30 \u00fczerinden 25 ise ve sizin tak\u0131m \u00fcyesi puanlaman\u0131za g\u00f6re ortalaman\u0131n alt\u0131nda bir katk\u0131da bulundu\u011funuz g\u00f6z\u00fck\u00fcyorsa, sizin proje puan\u0131n\u0131z 25\u2019ten k\u00fc\u00e7\u00fck olacakt\u0131r. Bu d\u00fc\u015f\u00fcr\u00fcm\u00fcn miktar\u0131 ile ilgili kolay bir kural yoktur.<br \/>\n<strong>Derste ula\u015f\u0131lmas\u0131 hedeflenenler:<\/strong><\/p>\n<ol>\n<li>\u0130lk kez programlamaya girecek kat\u0131l\u0131mc\u0131lara programlaman\u0131n temellerini \u00f6\u011frenebilece\u011fi bir ortam sa\u011flamak.<\/li>\n<li>Temel veri yap\u0131lar\u0131na giri\u015f yapmak<\/li>\n<li>Nesne y\u00f6nelimli programlamaya giri\u015f yapmak<\/li>\n<li>Python ve k\u00fct\u00fcphanelerini kullanarak tan\u0131mlay\u0131c\u0131 (descriptive) ve tahminci (predictive) veri analizi y\u00f6ntemleri geli\u015ftirebilmek<\/li>\n<li>Python ve k\u00fct\u00fcphanelerini kullanarak g\u00f6rselle\u015ftirme projelerini yapabilmek<\/li>\n<li>Python ve k\u00fct\u00fcphanelerini kullanarak u\u00e7tan uca, veri y\u00fckleme, veri \u00f6n i\u015fleme, veri d\u00f6n\u00fc\u015f\u00fcm\u00fc, veri modellemesi ve veri g\u00f6rselle\u015ftirmesi i\u015flemlerini yapabiliyor olmak.<\/li>\n<\/ol>\n<p><strong>Ders \u0130zlencesi:<\/strong><\/p>\n<ul>\n<li><strong>Hafta 1: Derse giri\u015f, yaz\u0131l\u0131mlar\u0131n tan\u0131t\u0131lmas\u0131, ders izlencesi ve tan\u0131\u015fma:\u00a0<\/strong>temel programlama teknikleri, de\u011fi\u015fken, d\u00f6ng\u00fclere giri\u015f\n<ul>\n<li><span style=\"color: #ff0000;\">\u00d6DEV 1:<\/span>\u00a0<a href=\"http:\/\/sadievrenseker.com\/wp-content\/uploads\/2017\/09\/odev_1.pdf\">http:\/\/sadievrenseker.com\/wp-content\/uploads\/2017\/09\/odev_1.pdf<\/a><\/li>\n<li>Son teslim tarihi 27 Ekim 2018 (ders saatine kadar) uzat\u0131lm\u0131\u015ft\u0131r.<\/li>\n<\/ul>\n<\/li>\n<li><strong>Hafta 2: Yap\u0131sal programlamaya (structural programming) giri\u015f<\/strong> : \u00a0ko\u015fullar (<em>if, else, elif:<\/em>) for d\u00f6ng\u00fcleri, range fonksiyonu,\u00a0ve fonksiyon kavram\u0131na ( <em>def f(x):<\/em> ) giri\u015f ve uygulamalar\u0131\n<ul>\n<li>Derste Yaz\u0131lan \u00d6rnek Kodlar:<\/li>\n<li>ile ilgili yaz\u0131lan 2. hafta kodlar\u0131 (indirmek i\u00e7in buraya t\u0131klay\u0131n &gt;&gt;&gt; <a href=\"http:\/\/sadievrenseker.com\/wp-content\/uploads\/2017\/09\/listeler_fonksiyonlar_donguler.zip\">listeler_fonksiyonlar_donguler<\/a>\u00a0 ):\n<ul>\n<li>if, else ve elif kullan\u0131m\u0131 ve ko\u015fullar : untitled.py<\/li>\n<li>If kavram\u0131, kullan\u0131c\u0131dan say\u0131 okumak ve int de\u011ferine d\u00f6n\u00fc\u015ft\u00fcrmek. Verilen bir 100&#8217;l\u00fck notun harf notuna d\u00f6n\u00fc\u015f\u00fcm\u00fc \u00f6rne\u011fi: ikinci.py<\/li>\n<li>D\u00f6ng\u00fc kavram\u0131 ve while, for d\u00f6ng\u00fcleri: ucuncu.py<\/li>\n<li>range ve liste kavramlar\u0131 ve for d\u00f6ng\u00fcs\u00fcn\u00fc kullanarak ortalama, toplam hesaplama: dort.py<\/li>\n<li>Kullan\u0131c\u0131dan -1 girilene kadar say\u0131 alan ve bu say\u0131lar\u0131n toplam\u0131n\u0131 d\u00f6nd\u00fcren kod (break ve continue kavramlar\u0131): bes.py<\/li>\n<li>Fibonacci serisini hesaplayan fonksiyon: alti.py<\/li>\n<li>Fakt\u00f6riyel ve Kombinasyon hesaplayan fonksiyonlar: yedi.py<\/li>\n<li>de\u011fi\u015fken ve liste \u00e7a\u011fr\u0131lmas\u0131 ve fonksiyon i\u00e7erisinde yap\u0131lan de\u011fi\u015fiklerin \u00e7a\u011fr\u0131lan yere etkisi (kopyalayarak \u00e7a\u011f\u0131rma ve referans ile \u00e7a\u011f\u0131rma (call by value, call by reference) kavarmlar\u0131: sekiz.py<\/li>\n<li>bir liste alarak listedeki sayilarin toplamini d\u00f6nd\u00fcren fonksiyon : dokuz.py<\/li>\n<li>Parametre say\u0131s\u0131 belirsiz parametreyi al\u0131p i\u015fleyen fonksiyon ( *l ) : on.py<\/li>\n<\/ul>\n<\/li>\n<\/ul>\n<\/li>\n<\/ul>\n<p><iframe loading=\"lazy\" title=\"PYTHONv3 Video 1: Dile ve E\u011fitime Giri\u015f\" width=\"960\" height=\"540\" src=\"https:\/\/www.youtube.com\/embed\/AaOv4BjN2UY?list=PLh9ECzBB8tJNTYpfiDs3PVlCZIwE9Gz0e\" frameborder=\"0\" allow=\"accelerometer; autoplay; clipboard-write; encrypted-media; gyroscope; picture-in-picture; web-share\" referrerpolicy=\"strict-origin-when-cross-origin\" allowfullscreen><\/iframe><\/p>\n<ul>\n<li><strong>Hafta 3: Veri yap\u0131lar\u0131na giri\u015f (Data structures) ve <\/strong><strong>Nesne Y\u00f6nelimli programlamaya giri\u015f<\/strong> (object oriented programming) : Nesne, kal\u0131t\u0131m (inheritance), kaps\u00fclleme (encapsulation), \u00e7ok \u015fekillilik (polymorphism) v.b. kavramlar.\u00a0temel veri yap\u0131lar\u0131n\u0131n \u00e7al\u0131\u015fma mant\u0131\u011f\u0131 ve kullan\u0131m alanlar\u0131, diziler, listeler, y\u0131\u011f\u0131n (stack), s\u0131ra (queue), a\u011fa\u00e7lar (trees) , haritalar (maps), v.b. kavramlar.\n<ul>\n<li><span style=\"color: #ff0000;\">\u00d6DEV 2:\u00a0<a href=\"http:\/\/sadievrenseker.com\/wp-content\/uploads\/2017\/09\/odev_2.pdf\">http:\/\/sadievrenseker.com\/wp-content\/uploads\/2017\/09\/odev_2.pdf<\/a><\/span><\/li>\n<li>\u00d6DEV 2 i\u00e7in son teslim tarihi 27 Ekim 2018 ders saatine kadard\u0131r.<\/li>\n<li><a href=\"http:\/\/sadievrenseker.com\/wp-content\/uploads\/2017\/09\/hafta3python_veriyapilari.zip\">Derste Yaz\u0131lan kodlar\u0131 indirmek i\u00e7in t\u0131klay\u0131n\u0131z.<\/a>(2017 y\u0131l\u0131ndaki kod \u00f6rnekleri)<\/li>\n<li><a href=\"http:\/\/sadievrenseker.com\/wp-content\/uploads\/2018\/09\/13ekim.py_.zip\">Derste Yaz\u0131lan Kodlar (2018) .<\/a>\n<ul>\n<li>liste_giris.py : listelerin veri yap\u0131s\u0131 olarak kullan\u0131lmas\u0131, temel liste fonksiyonlar\u0131, \u00e7ok boyutlu diziler ve listeler listesi kavram\u0131<\/li>\n<li>Kume: k\u00fcmeler (sets)<\/li>\n<li>sozluk.py: s\u00f6zl\u00fck (dictionary)<\/li>\n<li>sorular.py: Derste \u00e7\u00f6z\u00fclen \u00f6rnek sorular<\/li>\n<\/ul>\n<\/li>\n<\/ul>\n<\/li>\n<\/ul>\n<p><iframe loading=\"lazy\" title=\"Python Veri Yap\u0131lar\u0131 1: Listelere Genel Bak\u0131\u015f ve Baz\u0131 Fonksiyonlar\" width=\"960\" height=\"540\" src=\"https:\/\/www.youtube.com\/embed\/V7yZ69pgJKU?list=PLh9ECzBB8tJOoFYmIIiwFjgXDCD9uiD_i\" frameborder=\"0\" allow=\"accelerometer; autoplay; clipboard-write; encrypted-media; gyroscope; picture-in-picture; web-share\" referrerpolicy=\"strict-origin-when-cross-origin\" allowfullscreen><\/iframe><\/p>\n<ul>\n<li><strong>Hafta 4 &#8211; 5 (Devam): Veri analizine giri\u015f ve veri k\u00fcmelerinin y\u00f6netilmesi \/ y\u00fcklenmesi<\/strong>\n<ul>\n<li>Veri K\u00fcmeleri (dersten \u00f6nce indirmenizde fayda var): <a href=\"http:\/\/sadievrenseker.com\/wp-content\/uploads\/2017\/09\/hafta3_veriseti.zip\">indirmek i\u00e7in t\u0131klay\u0131n\u0131z.<\/a><\/li>\n<li>Derste kullan\u0131lacak IDE i\u00e7in: <a href=\"https:\/\/www.anaconda.com\">Anaconda.com<\/a><\/li>\n<li>\u00d6rneklerin \u00e7al\u0131\u015fma sonu\u00e7lar\u0131:<\/li>\n<li><a href=\"http:\/\/sadievrenseker.com\/wp-content\/uploads\/2017\/09\/hafta4_1.png\"><img loading=\"lazy\" decoding=\"async\" class=\"alignnone size-medium wp-image-1663\" src=\"http:\/\/sadievrenseker.com\/wp-content\/uploads\/2017\/09\/hafta4_1-300x167.png\" alt=\"\" width=\"300\" height=\"167\" srcset=\"https:\/\/sadievrenseker.com\/wp-content\/uploads\/2017\/09\/hafta4_1-300x167.png 300w, https:\/\/sadievrenseker.com\/wp-content\/uploads\/2017\/09\/hafta4_1-768x427.png 768w, https:\/\/sadievrenseker.com\/wp-content\/uploads\/2017\/09\/hafta4_1-1024x569.png 1024w, https:\/\/sadievrenseker.com\/wp-content\/uploads\/2017\/09\/hafta4_1.png 1318w\" sizes=\"auto, (max-width: 300px) 100vw, 300px\" \/><\/a> <a href=\"http:\/\/sadievrenseker.com\/wp-content\/uploads\/2017\/09\/hafta4_3.png\"><img loading=\"lazy\" decoding=\"async\" class=\"alignnone size-medium wp-image-1664\" src=\"http:\/\/sadievrenseker.com\/wp-content\/uploads\/2017\/09\/hafta4_3-300x147.png\" alt=\"\" width=\"300\" height=\"147\" srcset=\"https:\/\/sadievrenseker.com\/wp-content\/uploads\/2017\/09\/hafta4_3-300x147.png 300w, https:\/\/sadievrenseker.com\/wp-content\/uploads\/2017\/09\/hafta4_3-768x376.png 768w, https:\/\/sadievrenseker.com\/wp-content\/uploads\/2017\/09\/hafta4_3-1024x501.png 1024w, https:\/\/sadievrenseker.com\/wp-content\/uploads\/2017\/09\/hafta4_3.png 1312w\" sizes=\"auto, (max-width: 300px) 100vw, 300px\" \/><\/a><\/li>\n<li><span style=\"color: #ff0000;\"><strong>\u00d6dev 3:<\/strong> <\/span>Kaggle \u00fczerinde birer hesap a\u00e7\u0131n\u0131z ve ayr\u0131ca \u015fu tutorial&#8217;da bulunan ad\u0131mlar\u0131 4. b\u00f6l\u00fcme kadar (4. b\u00f6l\u00fcm hari\u00e7) yap\u0131n\u0131z ve kodlar\u0131n\u0131z\u0131 ve \u00e7\u0131kt\u0131lar\u0131n\u0131z\u0131 yollay\u0131n\u0131z: <a href=\"https:\/\/www.kaggle.com\/helgejo\/an-interactive-data-science-tutorial\">tutoriala eri\u015fmek i\u00e7in t\u0131klay\u0131n\u0131z<\/a><\/li>\n<li><a href=\"http:\/\/sadievrenseker.com\/wp-content\/uploads\/2017\/09\/cozumler1.py_.zip\">1. \u00d6devin \u00c7\u00f6z\u00fcm\u00fc<\/a><\/li>\n<li><a href=\"http:\/\/sadievrenseker.com\/wp-content\/uploads\/2017\/09\/cozumler1.py_.zip\">Derste Yaz\u0131lan Kodlar<\/a>\u00a0(2017 y\u0131l\u0131 i\u00e7in) (Kitab\u0131n 2. B\u00f6l\u00fcm\u00fcndeki ilk \u00f6rne\u011fi (bitli\/usa.gov veri k\u00fcmesi ile olan\u0131) yapt\u0131k ve \u00e7al\u0131\u015ft\u0131rd\u0131k. Notlanmayacak bir \u00f6dev olarak yine kitab\u0131n 2. b\u00f6l\u00fcm\u00fcndeki di\u011fer 2 veri k\u00fcmesini \u00e7al\u0131\u015ft\u0131rman\u0131z\u0131 tavsiye ederim.<\/li>\n<li><a href=\"http:\/\/sadievrenseker.com\/wp-content\/uploads\/2018\/09\/denemeler_20ekim2018.py_.zip\">Derste ya\u0131lan kodlar<\/a> (2018 y\u0131l\u0131 i\u00e7in)<\/li>\n<li><strong>Veri \u00d6n \u0130\u015fleme (Data Preprocessing)<\/strong>\n<ul>\n<li>Ders 5: Verinin Y\u00fcklenmesi\n<ul>\n<li><a href=\"http:\/\/www.bilkav.com\/wp-content\/uploads\/2018\/03\/veriler.csv\">Veri K\u00fcmesi: veriler.csv (indirmek i\u00e7in t\u0131tklay\u0131n\u0131z)<\/a><\/li>\n<\/ul>\n<\/li>\n<li>Ders 6: K\u00fct\u00fcphanelerin Y\u00fcklenmesi: NumPY, Pandas ve MathPlot Y\u00fcklenmesi<\/li>\n<li>Ders 7: Verinin i\u00e7eri al\u0131nmas\u0131 (data import) :\n<ul>\n<li><a href=\"http:\/\/www.bilkav.com\/wp-content\/uploads\/2018\/03\/veriyukleme.py_.zip\">Python Kodu: Veri Y\u00fckleme Python Kodu (indirmek i\u00e7in t\u0131klay\u0131n\u0131z)<\/a><\/li>\n<\/ul>\n<\/li>\n<li>Ders 8: Python: Nesne Y\u00f6nelimli programlama<\/li>\n<li>Ders 9: Eksik Veriler\n<ul>\n<li><a href=\"http:\/\/www.bilkav.com\/wp-content\/uploads\/2018\/03\/eksikveriler.csv\">Veri K\u00fcmesi: eksikveriler.csv (indirmek i\u00e7in t\u0131klay\u0131n\u0131z)<\/a><\/li>\n<li><a href=\"http:\/\/www.bilkav.com\/wp-content\/uploads\/2018\/03\/eksikveriler.py_.zip\">Python Kodu: Eksik Veri Tamamlama (Impuatiton) \u00d6rnek kodu<\/a><\/li>\n<\/ul>\n<\/li>\n<li>Ders 10: Kategorik Veriler\n<ul>\n<li><a href=\"http:\/\/www.bilkav.com\/wp-content\/uploads\/2018\/03\/kategorik.py_.zip\">Python Kodu: Kategorik veriler ve LabelEncoder ve OneHotEncoder Kullan\u0131m\u0131<\/a><\/li>\n<\/ul>\n<\/li>\n<li>Ders 11: Veri k\u00fcmelerinin birle\u015ftirilmesi ve DataFrame kavram\u0131\n<ul>\n<li><a href=\"http:\/\/www.bilkav.com\/wp-content\/uploads\/2018\/03\/veribirlestirme.py_.zip\">Python Kodu: Veri Birle\u015ftirme ve DataFrame kavram\u0131<\/a><\/li>\n<\/ul>\n<\/li>\n<li>Ders 12: Veri K\u00fcmesinin E\u011fitim ve Test olarak b\u00f6l\u00fcnmesi\n<ul>\n<li><a href=\"http:\/\/www.bilkav.com\/wp-content\/uploads\/2018\/03\/testegitimbolme.py_.zip\">Python Kodu: Veri K\u00fcmesini E\u011fitim ve Test k\u00fcmesi olarak b\u00f6lme kodu<\/a><\/li>\n<\/ul>\n<\/li>\n<li>Ders 13: \u00d6znitelik \u00d6l\u00e7ekleme\n<ul>\n<li><a href=\"http:\/\/www.bilkav.com\/wp-content\/uploads\/2018\/03\/veriolcekleme.py_.zip\">Python Kodu: Veri \u00d6l\u00e7ekleme<\/a><\/li>\n<\/ul>\n<\/li>\n<li>Ders 14: Veri \u00d6n i\u015fleme \u015eablonu\n<ul>\n<li><a href=\"http:\/\/www.bilkav.com\/wp-content\/uploads\/2018\/03\/verionislemesablonu.py_.zip\">Python Kodu: Veri \u00d6n \u0130\u015fleme \u015eablonu<\/a><\/li>\n<\/ul>\n<\/li>\n<\/ul>\n<\/li>\n<\/ul>\n<\/li>\n<li><strong>Hafta 6-7 : NumPy ve Pandas temelleri<\/strong> ve Tahminci Analiti\u011fe Giri\u015f (Predictive Analytics) temel dizi analizi, vekt\u00f6rize hesaplamalar, dosya i\u015flemleri ve do\u011frusal cebir (linear algebra), rasgele say\u0131 (random number) \u00fcretimi\u00a0<strong>\u00a0<\/strong><a href=\"http:\/\/sadievrenseker.com\/wp-content\/uploads\/2017\/09\/odev2_cozum.py_.zip\">\u00d6dev 2 \u00c7\u00f6z\u00fcm\u00fc\u00a0<\/a>\u00a0,\u00a0<span style=\"color: #ff0000;\">\u00d6dev 4:<\/span> <a href=\"https:\/\/www.labri.fr\/perso\/nrougier\/teaching\/numpy.100\/index.html\">NumPy problemleri ve \u00e7\u00f6z\u00fcmleri<\/a> (\u00e7\u00f6z\u00fcmleri deneyerek tek bir dosya halinde yollaman\u0131z yeterlidir)\n<ul>\n<li>Ders 15: Tahmin Problemleri ve Genel Giri\u015f<\/li>\n<li><strong>Do\u011frusal Regresyon<\/strong>\n<ul>\n<li>Ders 16: Veri K\u00fcmesinin indirilmesi\n<ul>\n<li><a href=\"http:\/\/www.bilkav.com\/wp-content\/uploads\/2018\/03\/satislar.csv\">Veri K\u00fcmesi: Aylara g\u00f6re Sat\u0131\u015f Verileri<\/a><\/li>\n<\/ul>\n<\/li>\n<li>Ders 17: Veri K\u00fcmesi ve Kodlar ile ilgili<\/li>\n<li>Ders 18: Do\u011frusal Regresyon Kavram\u0131na Giri\u015f<\/li>\n<li>Ders 19: Veri \u00d6n \u0130\u015fleme \u015eablonu ile Verinin Y\u00fcklenmesi\n<ul>\n<li><a href=\"http:\/\/www.bilkav.com\/wp-content\/uploads\/2018\/03\/dogrusalregresyonhazirlik.py_.zip\">Python Kodu: \u00d6n i\u015fleme \u015fablonunun y\u00fcklenmesi<\/a><\/li>\n<\/ul>\n<\/li>\n<li>Ders 20: Do\u011frusal Regresyon Modelinin \u0130n\u015fa Edilmesi\n<ul>\n<li><a href=\"http:\/\/www.bilkav.com\/wp-content\/uploads\/2018\/03\/dogrusalregresyonmodelinsasi.py_.zip\">Python Kodu: Do\u011frusal Regresyon Modeli<\/a><\/li>\n<\/ul>\n<\/li>\n<li>Ders 21: Do\u011frusal Regresyon Modelini Uygulayarak Tahmin\n<ul>\n<li><a href=\"http:\/\/www.bilkav.com\/wp-content\/uploads\/2018\/03\/dogrusalregresyon_tahmin.py_.zip\">Python Kodu: Do\u011frusal Regresyon ile Tahmin<\/a><\/li>\n<\/ul>\n<\/li>\n<li>Ders 22: Do\u011frusal Regresyon ve Verilerin G\u00f6rselle\u015ftirilmesi\n<ul>\n<li><a href=\"http:\/\/www.bilkav.com\/wp-content\/uploads\/2018\/03\/dogrusalregresyon_gorsellestirme.py_.zip\">Python Kodu: Veri ve Regresyon G\u00f6rselle\u015ftirme<\/a><\/li>\n<\/ul>\n<\/li>\n<li>Quiz 2: Basit Do\u011frusal Regresyon Sorular\u0131<\/li>\n<\/ul>\n<\/li>\n<li><strong>\u00c7oklu Do\u011frusal Regresyon<\/strong>\n<ul>\n<li>Ders 23: Veri K\u00fcmesi ve Problemin Tan\u0131m\u0131<\/li>\n<li>Ders 24: \u00c7oklu De\u011fi\u015fkenlerdeki Problemler ve \u00c7\u00f6z\u00fcmleri<\/li>\n<li>Ders 25:\u00a0Kukla De\u011fi\u015fken (Dummy Variable) ve Kukla De\u011fi\u015fken Tuza\u011f\u0131<\/li>\n<li>Ders 26: \u00c7al\u0131\u015fma \u00d6devi 1: P-Value<\/li>\n<li>Ders 27: P-Value<\/li>\n<li>Ders 28: De\u011fi\u015fken Se\u00e7imi ve Geri Eleme (Backward Elimination), \u0130leri Se\u00e7im (Forward Selection), \u00c7ift Y\u00f6nl\u00fc Se\u00e7im (Bidirectional Elimination) y\u00f6ntemleri<\/li>\n<li>Ders 29: \u00c7oklu Do\u011frusal Regresyon Kodlamas\u0131: Veri K\u00fcmesini Haz\u0131rlama\n<ul>\n<li><a href=\"http:\/\/www.bilkav.com\/wp-content\/uploads\/2018\/03\/pythton_mlr_hazirlik.py_.zip\">Python Kodu: \u00c7oklu Do\u011frusal Regresyon i\u00e7in Veri Haz\u0131rlama<\/a><\/li>\n<\/ul>\n<\/li>\n<li>Ders 30: \u00c7oklu Do\u011frusal Regresyon Kodlamas\u0131: Regresyon Modeli\n<ul>\n<li><a href=\"http:\/\/www.bilkav.com\/wp-content\/uploads\/2018\/03\/pythton_mlr_tahmin.py_.zip\">Python Kodu: \u00c7oklu Do\u011frusal Regresyon ile Problem \u00c7\u00f6z\u00fcm\u00fc<\/a><\/li>\n<\/ul>\n<\/li>\n<li>Ders 31: Geri Eleme Y\u00f6ntemi (Backward Elimination)\n<ul>\n<li><a href=\"http:\/\/www.bilkav.com\/wp-content\/uploads\/2018\/03\/gerieleme.py_.zip\">Python Kodu: Geri Eleme y\u00f6nteminin Python ile kodlanmas\u0131<\/a><\/li>\n<\/ul>\n<\/li>\n<li>\u00d6dev 1: \u00c7oklu Do\u011frusal Regresyon (Ders 32)\n<ul>\n<li><a href=\"http:\/\/www.bilkav.com\/wp-content\/uploads\/2018\/03\/odev_tenis.csv\">\u00d6dev i\u00e7in Veri K\u00fcmesi<\/a><\/li>\n<li><a href=\"http:\/\/www.bilkav.com\/wp-content\/uploads\/2018\/03\/odev_cozum_hazirlik.py_-1.zip\">G\u00fcncellendi : Haz\u0131rl\u0131k Kodu<\/a><\/li>\n<li><del><a href=\"http:\/\/www.bilkav.com\/wp-content\/uploads\/2018\/03\/odev_cozum_hazirlik.py_.zip\">\u00d6dev i\u00e7in Haz\u0131rl\u0131k Kodu<\/a><\/del><\/li>\n<\/ul>\n<\/li>\n<li>\u00d6dev 1: \u00c7\u00f6z\u00fcm\u00fc 1. Par\u00e7a: Veri Haz\u0131rlama ve Do\u011frusal Regresyon (Ders 33)<\/li>\n<li>\u00d6dev 1: \u00c7\u00f6z\u00fcm\u00fc 2. Par\u00e7a: Geri Eleme Y\u00f6ntemi ile (Backward Elimination) (Ders 34)\n<ul>\n<li><a href=\"http:\/\/www.bilkav.com\/wp-content\/uploads\/2018\/03\/odev_cozum.py_.zip\">\u00c7\u00f6z\u00fcm\u00fcn Python Kodu<\/a><\/li>\n<\/ul>\n<\/li>\n<li>Quiz 3: \u00c7oklu Do\u011frusal Regresyon<\/li>\n<\/ul>\n<\/li>\n<li><strong>Polinomal Regresyon<\/strong>\n<ul>\n<li>Ders 35: Veri K\u00fcmesi, Kavram\u0131n ve Problemin Tan\u0131m\u0131\n<ul>\n<li><a href=\"http:\/\/www.bilkav.com\/wp-content\/uploads\/2018\/03\/maaslar.csv\">Veri K\u00fcmesi: Maaslar.csv<\/a><\/li>\n<\/ul>\n<\/li>\n<li>Ders 36: Polinom Regresyonun Python ile Uygulamas\u0131\n<ul>\n<li><a href=\"http:\/\/www.bilkav.com\/wp-content\/uploads\/2018\/03\/polinom_regresyon.py_.zip\">Python Kodu: Polinom Regresyon uygulamas\u0131<\/a><\/li>\n<\/ul>\n<\/li>\n<li>Ders 37: Python ile Polinom Regresyon \u015eablonu\n<ul>\n<li><a href=\"http:\/\/www.bilkav.com\/wp-content\/uploads\/2018\/03\/regresyon_sablonu.py_.zip\">Python Kodu: Polinom regresyon \u015fablonu<\/a><\/li>\n<\/ul>\n<\/li>\n<\/ul>\n<\/li>\n<\/ul>\n<\/li>\n<li><strong>Hafta 8-9: Tan\u0131mlay\u0131c\u0131 ve Tahminci istatisti\u011fe giri\u015f<\/strong>\u00a0ve Devam (descriptive statistics), Pandas k\u00fct\u00fcphanesi ve veri yap\u0131lar\u0131 ve Sci-Kit Learn\n<ul>\n<li><a href=\"http:\/\/sadievrenseker.com\/wp-content\/uploads\/2017\/11\/data.zip\">\u00d6rnek Veri K\u00fcmeleri\u00a0<\/a><\/li>\n<li><a href=\"http:\/\/sadievrenseker.com\/wp-content\/uploads\/2017\/09\/pandas_screenshot.png\"><img loading=\"lazy\" decoding=\"async\" class=\"alignnone size-medium wp-image-1723\" src=\"http:\/\/sadievrenseker.com\/wp-content\/uploads\/2017\/09\/pandas_screenshot-262x300.png\" alt=\"\" width=\"262\" height=\"300\" srcset=\"https:\/\/sadievrenseker.com\/wp-content\/uploads\/2017\/09\/pandas_screenshot-262x300.png 262w, https:\/\/sadievrenseker.com\/wp-content\/uploads\/2017\/09\/pandas_screenshot-768x878.png 768w, https:\/\/sadievrenseker.com\/wp-content\/uploads\/2017\/09\/pandas_screenshot-895x1024.png 895w, https:\/\/sadievrenseker.com\/wp-content\/uploads\/2017\/09\/pandas_screenshot.png 1170w\" sizes=\"auto, (max-width: 262px) 100vw, 262px\" \/><\/a><\/li>\n<li><a href=\"http:\/\/sadievrenseker.com\/wp-content\/uploads\/2017\/09\/Untitled.ipynb_.zip\">Derste yaz\u0131lan PANDAS k\u00fct\u00fcphanesi kodlar\u0131n\u0131n Jupyter Notebook kodlar\u0131\u00a0<\/a><\/li>\n<li><a href=\"http:\/\/sadievrenseker.com\/wp-content\/uploads\/2017\/09\/Untitled.py_.zip\">Derste Yaz\u0131lan PANDAS k\u00fct\u00fcphanesi kodlar\u0131n\u0131n python uzant\u0131l\u0131 kodlar\u0131<\/a><\/li>\n<li><a href=\"http:\/\/sadievrenseker.com\/wp-content\/uploads\/2017\/09\/Untitled-2.html\">Derste Yaz\u0131lan PANDAS k\u00fct\u00fcphanesi kodlar\u0131n\u0131n web d\u00f6k\u00fcm\u00fc<\/a><\/li>\n<li><span style=\"color: #ff0000;\">\u00d6dev 5:<\/span> Verilen veri k\u00fcmesi \u00fczerinde a\u015fa\u011f\u0131da say\u0131lan g\u00f6revleri PANDAS k\u00fct\u00fcphanesini kullanarak yerine getiriniz:\n<ul>\n<li><a href=\"http:\/\/sadievrenseker.com\/wp-content\/uploads\/2017\/09\/telefon.csv\">Veri k\u00fcmesini indirmek i\u00e7in t\u0131klay\u0131n\u0131z<\/a> (toplam 830 kay\u0131tta yap\u0131lan mobil g\u00f6r\u00fc\u015fme ve veri trafi\u011fi tutulmu\u015ftur)<\/li>\n<li><strong>G\u00f6rev 1:<\/strong> Aylara g\u00f6re toplam arama say\u0131lar\u0131n\u0131 listeleyiniz\n<ul>\n<li>\u0130PUCU: dateutil k\u00fct\u00fcphanesini kullanarak tarihleri ay ve y\u0131l \u015feklinde d\u00f6n\u00fc\u015ft\u00fcrebilirsiniz:<\/li>\n<li><a href=\"http:\/\/sadievrenseker.com\/wp-content\/uploads\/2017\/09\/dateutil.png\"><img loading=\"lazy\" decoding=\"async\" class=\"alignnone wp-image-1725\" src=\"http:\/\/sadievrenseker.com\/wp-content\/uploads\/2017\/09\/dateutil-1024x171.png\" alt=\"\" width=\"696\" height=\"116\" srcset=\"https:\/\/sadievrenseker.com\/wp-content\/uploads\/2017\/09\/dateutil-1024x171.png 1024w, https:\/\/sadievrenseker.com\/wp-content\/uploads\/2017\/09\/dateutil-300x50.png 300w, https:\/\/sadievrenseker.com\/wp-content\/uploads\/2017\/09\/dateutil-768x128.png 768w, https:\/\/sadievrenseker.com\/wp-content\/uploads\/2017\/09\/dateutil.png 1424w\" sizes=\"auto, (max-width: 696px) 100vw, 696px\" \/><\/a><\/li>\n<li>\u00c7\u0131kt\u0131 a\u015fa\u011f\u0131daki \u015fekilde olacakt\u0131r:<\/li>\n<li><a href=\"http:\/\/sadievrenseker.com\/wp-content\/uploads\/2017\/09\/aramasayilari.png\"><img loading=\"lazy\" decoding=\"async\" class=\"alignnone wp-image-1726\" src=\"http:\/\/sadievrenseker.com\/wp-content\/uploads\/2017\/09\/aramasayilari.png\" alt=\"\" width=\"115\" height=\"102\" \/><\/a><\/li>\n<\/ul>\n<\/li>\n<li><strong>G\u00f6rev 2:<\/strong> Aylara g\u00f6re ortalama g\u00f6r\u00fc\u015fme s\u00fcrelerini listeleyiniz\n<ul>\n<li>\u00c7\u0131kt\u0131 a\u015fa\u011f\u0131daki \u015fekilde olacakt\u0131r:<\/li>\n<li><a href=\"http:\/\/sadievrenseker.com\/wp-content\/uploads\/2017\/09\/aylaragore_sure.png\"><img loading=\"lazy\" decoding=\"async\" class=\"alignnone wp-image-1727\" src=\"http:\/\/sadievrenseker.com\/wp-content\/uploads\/2017\/09\/aylaragore_sure.png\" alt=\"\" width=\"230\" height=\"99\" srcset=\"https:\/\/sadievrenseker.com\/wp-content\/uploads\/2017\/09\/aylaragore_sure.png 436w, https:\/\/sadievrenseker.com\/wp-content\/uploads\/2017\/09\/aylaragore_sure-300x129.png 300w\" sizes=\"auto, (max-width: 230px) 100vw, 230px\" \/><\/a><\/li>\n<\/ul>\n<\/li>\n<li><strong>G\u00f6rev 3:<\/strong> Aylara g\u00f6re toplam g\u00f6r\u00fc\u015fme, minimum g\u00f6r\u00fc\u015fme ve maksimum g\u00f6r\u00fc\u015fme s\u00fcrelerini bir tablo halinde d\u00f6k\u00fcn\u00fcz:<\/li>\n<li><a href=\"http:\/\/sadievrenseker.com\/wp-content\/uploads\/2017\/09\/aylaragore_sure_df.png\"><img loading=\"lazy\" decoding=\"async\" class=\"alignnone wp-image-1728\" src=\"http:\/\/sadievrenseker.com\/wp-content\/uploads\/2017\/09\/aylaragore_sure_df.png\" alt=\"\" width=\"404\" height=\"209\" srcset=\"https:\/\/sadievrenseker.com\/wp-content\/uploads\/2017\/09\/aylaragore_sure_df.png 642w, https:\/\/sadievrenseker.com\/wp-content\/uploads\/2017\/09\/aylaragore_sure_df-300x155.png 300w\" sizes=\"auto, (max-width: 404px) 100vw, 404px\" \/><\/a><\/li>\n<li><strong>G\u00f6rev 4:<\/strong> veri, g\u00f6r\u00fc\u015fme ve sms bilgilerinin her birisi i\u00e7in en fazla g\u00f6r\u00fc\u015fme yap\u0131lan aylar\u0131 s\u0131ralay\u0131n\u0131z.<\/li>\n<li><a href=\"https:\/\/www.shanelynn.ie\/summarising-aggregation-and-grouping-data-in-python-pandas\/\">Yukar\u0131daki g\u00f6revler i\u00e7in bu web sitesinden faydalanabilirsiniz:\u00a0<\/a><\/li>\n<\/ul>\n<\/li>\n<li>U\u00e7tan Uca Veri Bilimi S\u00fcre\u00e7leri (Knime ve Rapid Miner&#8217;a giri\u015f ve s\u00fcre\u00e7 analizi)\n<ul>\n<li><a href=\"https:\/\/en.wikipedia.org\/wiki\/Cross-industry_standard_process_for_data_mining\">CRISP-DM<\/a><\/li>\n<li><a href=\"https:\/\/en.wikipedia.org\/wiki\/SEMMA\">SEMMA<\/a><\/li>\n<li><a href=\"https:\/\/en.wikipedia.org\/wiki\/Data_mining\">KDD<\/a><\/li>\n<\/ul>\n<\/li>\n<li>Veri Bilimi problem tipleri\n<ul>\n<li><a href=\"https:\/\/en.wikipedia.org\/wiki\/Statistical_classification\">S\u0131n\u0131fland\u0131rma (Classification)<\/a><\/li>\n<li><a href=\"https:\/\/en.wikipedia.org\/wiki\/Prediction\">Tahmin (Prediction)<\/a><\/li>\n<li>B\u00f6l\u00fctleme (K\u00fcmeleme, Clustering)<\/li>\n<li><a href=\"https:\/\/en.wikipedia.org\/wiki\/Association_rule_learning\">Birliktelik Kural \u00c7\u0131kar\u0131m\u0131 (Association Rule Mining)<\/a><\/li>\n<\/ul>\n<\/li>\n<li>S\u0131n\u0131fland\u0131rma Problemlerine Genel Giri\u015f<\/li>\n<li><strong>Lojistik Regresyon (Logistic Regression)<\/strong>\n<ul>\n<li>Lojistik Regresyon\u2019a giri\u015f<\/li>\n<li>Python ile Lojistik Regresyon Kodlama\n<ul>\n<li><a href=\"http:\/\/www.bilkav.com\/wp-content\/uploads\/2018\/03\/lr.py_.zip\">Python Kodu: Lojistik Regresyon<\/a><\/li>\n<\/ul>\n<\/li>\n<li>Confusion Matrix ve S\u0131n\u0131fland\u0131rma \u015fablonu\n<ul>\n<li><a href=\"http:\/\/www.bilkav.com\/wp-content\/uploads\/2018\/03\/lr_confusion.zip\">Python Kodu: S\u0131n\u0131fland\u0131rma \u015fablonu ve kar\u0131\u015f\u0131kl\u0131k matrisi<\/a><\/li>\n<\/ul>\n<\/li>\n<\/ul>\n<\/li>\n<li><strong>K-En Yak\u0131n Kom\u015fu (K-NN)<\/strong>\n<ul>\n<li>K-NN Algoritmas\u0131<\/li>\n<li>Python ile K-NN kodlamas\u0131\n<ul>\n<li><a href=\"http:\/\/www.bilkav.com\/wp-content\/uploads\/2018\/03\/knn.py_.zip\">Python Kodu: K-NN<\/a><\/li>\n<\/ul>\n<\/li>\n<li>Mesefe Algoritmalar\u0131 (Distance Metrics)\n<ul>\n<li>Python Kodu: Mesafe algoritmalar\u0131<\/li>\n<\/ul>\n<\/li>\n<li>Quiz: K-NN<\/li>\n<\/ul>\n<\/li>\n<li><strong>Destek Vekt\u00f6r Makineleri (Support Vector Machine)<\/strong>\n<ul>\n<li>Kavrama ve Problemlere Giri\u015f<\/li>\n<li>Python ile SVM uygulamas\u0131 ve s\u0131n\u0131fland\u0131rma\n<ul>\n<li><a href=\"http:\/\/www.bilkav.com\/wp-content\/uploads\/2018\/03\/svm.py_.zip\">Python Kodu: SVM uygulamas\u0131<\/a><\/li>\n<\/ul>\n<\/li>\n<\/ul>\n<\/li>\n<li><strong>Destek Vekt\u00f6r Makinelerinde \u00c7ekirdek kullan\u0131m\u0131<\/strong>\n<ul>\n<li>\u00c7ekirdek hilesi (kernel trick)<\/li>\n<li>Python ile \u00c7ekirdek fonksiyonlar\u0131 ve SVM\n<ul>\n<li><a href=\"http:\/\/www.bilkav.com\/wp-content\/uploads\/2018\/03\/svm.py_.zip\">Python Kod: SVM ve \u00c7ekirdek Hilesi<\/a><\/li>\n<\/ul>\n<\/li>\n<\/ul>\n<\/li>\n<li><strong>Naif Bayes<\/strong>\n<ul>\n<li>Bayes teoremi, Naive Bayes i\u00e7in Algoritman\u0131n ve problemlerin tan\u0131m\u0131,\u00a0Say\u0131sal \u00d6rnek \u00e7\u00f6z\u00fcm\u00fc<\/li>\n<li>Python ile Naive Bayes algoritmas\u0131n\u0131n kodlanmas\u0131\n<ul>\n<li><a href=\"http:\/\/www.bilkav.com\/wp-content\/uploads\/2018\/03\/nb.py_.zip\">Python Kodu : Naive Bayes<\/a><\/li>\n<\/ul>\n<\/li>\n<\/ul>\n<\/li>\n<li><strong>Karar A\u011fa\u00e7lar\u0131<\/strong>\n<ul>\n<li>Karar a\u011fa\u00e7lar\u0131na giri\u015f ve s\u0131n\u0131fland\u0131rma problemleri<\/li>\n<li>Python ile karar a\u011fa\u00e7lar\u0131n\u0131n kodlanmas\u0131\n<ul>\n<li><a href=\"http:\/\/www.bilkav.com\/wp-content\/uploads\/2018\/03\/dt.py_-1.zip\">Python Kodu : Decision Tree<\/a><\/li>\n<\/ul>\n<\/li>\n<\/ul>\n<\/li>\n<li><strong>Rassal A\u011fa\u00e7lar (Random Forest)<\/strong>\n<ul>\n<li>Rassal Ormanlar\u0131n, s\u0131n\u0131fland\u0131rma problemlerine uygulanmas\u0131<\/li>\n<li>Python ile Rassal Orman kodlamas\u0131\n<ul>\n<li><a href=\"http:\/\/www.bilkav.com\/wp-content\/uploads\/2018\/03\/rfc.py_.zip\">Python Kodu: Random Forest<\/a><\/li>\n<\/ul>\n<\/li>\n<\/ul>\n<\/li>\n<li><strong>S\u0131n\u0131fland\u0131rma Algoritmalar\u0131n\u0131n De\u011ferlendirilmesi<\/strong>\n<ul>\n<li>Confusion Matris<\/li>\n<li>Flase Positive ve False Negative Kavramlar\u0131<\/li>\n<li>Netlik\/do\u011fruluk (accuracy) paradoksu<\/li>\n<li>ROC e\u011frisi<\/li>\n<\/ul>\n<\/li>\n<li><strong>\u015eablon<\/strong>\n<ul>\n<li>S\u0131n\u0131fland\u0131rma \u015eablonu\n<ul>\n<li><a href=\"http:\/\/www.bilkav.com\/wp-content\/uploads\/2018\/03\/sablon.py_.zip\">Python Kodu: \u015eablon<\/a><\/li>\n<\/ul>\n<\/li>\n<li>S\u0131n\u0131fland\u0131rma Algoritmalar\u0131n\u0131n Kar\u015f\u0131la\u015ft\u0131r\u0131lmas\u0131 ve \u00d6zet\n<ul>\n<li><a href=\"http:\/\/www.bilkav.com\/wp-content\/uploads\/2018\/03\/udemy_siniflandirma_karsilastirma.pdf\">\u00d6zet tablo<\/a><\/li>\n<\/ul>\n<\/li>\n<\/ul>\n<\/li>\n<\/ul>\n<\/li>\n<\/ul>\n<p style=\"text-align: center;\"><a href=\"https:\/\/www.udemy.com\/veribilimi\/\">UDEMY : U\u00e7tan Uca Veri Bilimi (Knime ile)<\/a><\/p>\n<p><img loading=\"lazy\" decoding=\"async\" class=\"alignnone size-medium aligncenter\" src=\"https:\/\/udemy-images.udemy.com\/course\/480x270\/1481852_38c7_2.jpg\" width=\"480\" height=\"270\" \/><\/p>\n<ul>\n<li><strong>Hafta 10:<\/strong> SCI-KIT Learn K\u00fct\u00fcphanesine giri\u015f ve makine \u00f6\u011frenme algoritmalar\u0131 (Rapid Miner, Knime ve Python k\u00fct\u00fcphanelerinin kar\u015f\u0131la\u015ft\u0131rmal\u0131 \u00e7al\u0131\u015ft\u0131r\u0131lmas\u0131)\n<ul>\n<li>Yaz\u0131lan \u00d6rnek kodlar (cinsiyet excel dosyas\u0131ndan makine \u00f6\u011frenmesi ve s\u0131n\u0131fland\u0131rma \u00f6rnekleri), a\u015fa\u011f\u0131daki algoritmalar i\u00e7in \u00e7al\u0131\u015fmaktad\u0131r.\n<ul>\n<li><a href=\"https:\/\/en.wikipedia.org\/wiki\/Decision_tree_learning\">Karar A\u011fac\u0131 (Decision Tree)<\/a><\/li>\n<li><a href=\"https:\/\/en.wikipedia.org\/wiki\/Naive_Bayes_classifier\">Naive Bayes (GaussianNB)<\/a><\/li>\n<li><a href=\"https:\/\/en.wikipedia.org\/wiki\/Logistic_regression\">Logistic Regression<\/a><\/li>\n<li><a href=\"https:\/\/en.wikipedia.org\/wiki\/K-nearest_neighbors_algorithm\">KNN<\/a><\/li>\n<\/ul>\n<\/li>\n<li><a href=\"http:\/\/sadievrenseker.com\/wp-content\/uploads\/2017\/09\/ders10.zip\">\u00d6rnek Kod 1: Cinsiyet\u00a0<\/a><\/li>\n<li><a href=\"http:\/\/sadievrenseker.com\/wp-content\/uploads\/2017\/09\/cinsiyet.png\"><img loading=\"lazy\" decoding=\"async\" class=\"alignnone size-medium wp-image-1958\" src=\"http:\/\/sadievrenseker.com\/wp-content\/uploads\/2017\/09\/cinsiyet-300x145.png\" alt=\"\" width=\"300\" height=\"145\" srcset=\"https:\/\/sadievrenseker.com\/wp-content\/uploads\/2017\/09\/cinsiyet-300x145.png 300w, https:\/\/sadievrenseker.com\/wp-content\/uploads\/2017\/09\/cinsiyet.png 706w\" sizes=\"auto, (max-width: 300px) 100vw, 300px\" \/><\/a><\/li>\n<li><a href=\"http:\/\/sadievrenseker.com\/wp-content\/uploads\/2017\/09\/ders10_emlak.zip\">\u00d6rnek Kod 2: Emlak<\/a><\/li>\n<li><a href=\"http:\/\/sadievrenseker.com\/wp-content\/uploads\/2017\/09\/emlak.png\"><img loading=\"lazy\" decoding=\"async\" class=\"alignnone size-medium wp-image-1959\" src=\"http:\/\/sadievrenseker.com\/wp-content\/uploads\/2017\/09\/emlak-287x300.png\" alt=\"\" width=\"287\" height=\"300\" srcset=\"https:\/\/sadievrenseker.com\/wp-content\/uploads\/2017\/09\/emlak-287x300.png 287w, https:\/\/sadievrenseker.com\/wp-content\/uploads\/2017\/09\/emlak.png 764w\" sizes=\"auto, (max-width: 287px) 100vw, 287px\" \/><\/a><\/li>\n<li><strong><span style=\"color: #ff0000;\">\u00d6dev 6:<\/span><\/strong>\n<ul>\n<li><strong>G\u00f6rev 1:<\/strong> Titanic veri k\u00fcmesini y\u00fckleyerek derste \u00fczerinden ge\u00e7ilen algoritmalardan en az birisi ile hayatta kalan veya kalmayanlar\u0131 tahmin etmeye (s\u0131n\u0131fland\u0131rmaya) \u00e7al\u0131\u015f\u0131n.<\/li>\n<li><strong>G\u00f6rev 2:<\/strong> Derste i\u015flenen b\u00fct\u00fcn algoritmalar\u0131 deneyin ve hangisinin en ba\u015far\u0131l\u0131 oldu\u011funu yorumlay\u0131n (bir iki sat\u0131r yazarak anlat\u0131n).<\/li>\n<li><strong>G\u00f6rev 3:<\/strong> Bu i\u015flemler s\u0131ras\u0131nda b\u00fct\u00fcn verileri (say\u0131sal veya nominal) kullan\u0131n (herhangi bir kolonu d\u0131\u015far\u0131da b\u0131rakmay\u0131n, eksik veya kirli veri varsa \u00f6nizlemeye tabi tutun, kulland\u0131\u011f\u0131n\u0131z algoritma, veri tipi ile uyumlu de\u011filse veriyi uyumlu hale d\u00f6n\u00fc\u015ft\u00fcr\u00fcn).<\/li>\n<\/ul>\n<\/li>\n<\/ul>\n<\/li>\n<li><strong>Hafta 11\u00a0<\/strong>\n<ul>\n<li>SCI-Kit Learn ile a priori algorithmas\u0131 ve birliktelik kural \u00e7\u0131kar\u0131m\u0131<\/li>\n<li>B\u00f6l\u00fctleme-K\u00fcmeleme \u00f6rnekleri ve kodlar\u0131 (clustering)\n<ul>\n<li>Hata \u00f6l\u00e7\u00fcm y\u00f6ntemleri : Root Mean Square Error (RMSE), R2 Score , RAE, MAE<\/li>\n<li>K-Means Algoritmas\u0131 ve Kodlamas\u0131<\/li>\n<li><a href=\"http:\/\/sadievrenseker.com\/wp-content\/uploads\/2017\/09\/sphx_glr_plot_cluster_comparison_0011.png\"><img loading=\"lazy\" decoding=\"async\" class=\"alignnone size-large wp-image-1986\" src=\"http:\/\/sadievrenseker.com\/wp-content\/uploads\/2017\/09\/sphx_glr_plot_cluster_comparison_0011-1024x610.png\" alt=\"\" width=\"960\" height=\"572\" srcset=\"https:\/\/sadievrenseker.com\/wp-content\/uploads\/2017\/09\/sphx_glr_plot_cluster_comparison_0011-1024x610.png 1024w, https:\/\/sadievrenseker.com\/wp-content\/uploads\/2017\/09\/sphx_glr_plot_cluster_comparison_0011-300x179.png 300w, https:\/\/sadievrenseker.com\/wp-content\/uploads\/2017\/09\/sphx_glr_plot_cluster_comparison_0011-768x457.png 768w\" sizes=\"auto, (max-width: 960px) 100vw, 960px\" \/><\/a><\/li>\n<\/ul>\n<\/li>\n<li>k-Fold Cross Validation ve Leave One Out y\u00f6ntemleri<\/li>\n<li>Linear Modeller ve Linear Regression, Polynomial Regression<\/li>\n<li>B\u00f6l\u00fctleme (k\u00fcmeleme) problemlerine genel giri\u015f ve kullan\u0131m alanlar\u0131<\/li>\n<li><strong>B\u00f6l\u00fcm 5.1: K-Orta Algoritmas\u0131 (K-Means)<\/strong>\n<ul>\n<li>Kavrama ve algoritmaya giri\u015f<\/li>\n<li>Rassal Ba\u015flang\u0131\u00e7 Tuza\u011f\u0131<\/li>\n<li>K-Means algoritmas\u0131nda k\u00fcme say\u0131s\u0131na karar verilmesi<\/li>\n<li>Python ile K-Means algoritmas\u0131n\u0131n kodlanmas\u0131\n<ul>\n<li><a href=\"http:\/\/www.bilkav.com\/wp-content\/uploads\/2018\/03\/musteriler.csv\">Veri Dosyas\u0131<\/a><\/li>\n<li><a href=\"http:\/\/www.bilkav.com\/wp-content\/uploads\/2018\/03\/kmeans.py_.zip\">Python Kodu<\/a><\/li>\n<\/ul>\n<\/li>\n<li>Test : K-Means<\/li>\n<\/ul>\n<\/li>\n<li><strong>B\u00f6l\u00fcm 5.2: Hiyerar\u015fik B\u00f6l\u00fctleme<\/strong>\n<ul>\n<li>Hiyerar\u015fik k\u00fcmeleme kavram\u0131na giri\u015f<\/li>\n<li>Dendrogram kavram\u0131 ve hiyerar\u015fik k\u00fcmeleme kullan\u0131m\u0131<\/li>\n<li>Python ile Hiyerar\u015fik k\u00fcmeleme\n<ul>\n<li><a href=\"http:\/\/www.bilkav.com\/wp-content\/uploads\/2018\/03\/hc.py_.zip\">Python Kodu<\/a><\/li>\n<\/ul>\n<\/li>\n<li>Test: Hiyerar\u015fik B\u00f6l\u00fctleme \/ K\u00fcmeleme<\/li>\n<\/ul>\n<\/li>\n<li><a href=\"http:\/\/www.bilkav.com\/wp-content\/uploads\/2018\/03\/kumeleme_ozet.pdf\">B\u00f6l\u00fcm \u00d6zeti ve Modellerin Kar\u015f\u0131la\u015ft\u0131rmas\u0131<\/a><\/li>\n<li><\/li>\n<\/ul>\n<\/li>\n<li>Hafta 12 : Birliktelik Kural \u00c7\u0131kar\u0131m\u0131\n<ul>\n<li><strong>B\u00f6l\u00fcm 6.1: Apriori Algoritmas\u0131<\/strong>\n<ul>\n<li>Birliktelik Kural \u00c7\u0131kar\u0131m\u0131na ve Algoritmaya giri\u015f ve algoritman\u0131n \u00e7al\u0131\u015fmas\u0131<\/li>\n<li>Algoritman\u0131n Python ile kodlanmas\u0131\n<ul>\n<li><a href=\"http:\/\/www.bilkav.com\/wp-content\/uploads\/2018\/03\/Archive.zip\">Python Kodu ve K\u00fct\u00fcphane<\/a><\/li>\n<li><a href=\"http:\/\/www.bilkav.com\/wp-content\/uploads\/2018\/03\/sepet.csv\">Veriler : sepet.csv<\/a><\/li>\n<\/ul>\n<\/li>\n<\/ul>\n<\/li>\n<li><strong>B\u00f6l\u00fcm 6.2: Eclat Algoritmas\u0131<\/strong>\n<ul>\n<li>Algoritman\u0131n \u00e7al\u0131\u015fmas\u0131<\/li>\n<\/ul>\n<\/li>\n<\/ul>\n<\/li>\n<li><strong>Hafta 13:Peki\u015ftirmeli \/ Takviyeli \u00d6\u011frenme (Reinforced Learning)<\/strong>\n<ul>\n<li>Peki\u015ftirmeli \/ Takviyeli \u00d6\u011frenme (Reinforced Learning) Kavram\u0131na Giri\u015f<\/li>\n<li>A\/B Testi ve \u00c7ok Kollu Haydut Problemi (Multi Armed Bandit)<\/li>\n<li><strong>B\u00f6l\u00fcm 7.1. UCB<\/strong>\n<ul>\n<li>\u00dcst G\u00fcven S\u0131n\u0131r\u0131 (Upper Confidence Boun, UCB) Yakla\u015f\u0131m\u0131<\/li>\n<li>Rasgele \u00d6rnekleme Yakla\u015f\u0131m\u0131, Probleme ve UCB Algoritmas\u0131na giri\u015f\n<ul>\n<li><a href=\"http:\/\/www.bilkav.com\/wp-content\/uploads\/2018\/03\/random_sampling.zip\">Python Kodu: Rasgele \u00d6rnekleme (Random Sampling)<\/a><\/li>\n<\/ul>\n<\/li>\n<li>UCB Algoritmas\u0131n\u0131n Python ile kodlanmas\u0131\n<ul>\n<li><a href=\"http:\/\/www.bilkav.com\/wp-content\/uploads\/2018\/03\/UCB.zip\">Python Kodu: UCB ile peki\u015ftirmeli \/ takviyeli \u00f6\u011frenme<\/a><\/li>\n<\/ul>\n<\/li>\n<\/ul>\n<\/li>\n<li><strong>B\u00f6l\u00fcm 7.2. Thompson \u00d6rneklemesi (Sampling)<\/strong>\n<ul>\n<li>Thompson Sampling Yakla\u015f\u0131m\u0131<\/li>\n<li>Algoritmalar\u0131n Kar\u015f\u0131la\u015ft\u0131r\u0131lmas\u0131 (UCB ve Thompson S)<\/li>\n<li><a href=\"http:\/\/www.bilkav.com\/wp-content\/uploads\/2018\/03\/Archive-1.zip\">Python ile kodlama<\/a><\/li>\n<\/ul>\n<\/li>\n<\/ul>\n<\/li>\n<\/ul>\n<p><iframe loading=\"lazy\" title=\"Neural Network 1 : E\u011fitime ve Kavramlara Giri\u015f\" width=\"960\" height=\"540\" src=\"https:\/\/www.youtube.com\/embed\/B5MmXmMMuvI?list=PLh9ECzBB8tJNI6m-K0XjIvqth3GSYLy_5\" frameborder=\"0\" allow=\"accelerometer; autoplay; clipboard-write; encrypted-media; gyroscope; picture-in-picture; web-share\" referrerpolicy=\"strict-origin-when-cross-origin\" allowfullscreen><\/iframe><\/p>\n<ul>\n<li><strong>Hafta 14 Derin \u00d6\u011frenme:<\/strong>\n<ul>\n<li><strong>Derin \u00d6\u011frenme (Deep Learning)<\/strong>\n<ul>\n<li>Yapay Sinir A\u011flar\u0131na Giri\u015f (Artificial Neural Networks)<\/li>\n<li>Aktivasyon Fonksiyonlar\u0131 (Activation Functions)<\/li>\n<li>Katman Kavram\u0131 ve \u00c7al\u0131\u015fan bir Yapay Sinir A\u011f\u0131<\/li>\n<li>XOR Problemi ve \u00c7\u00f6z\u00fcm olacak YSA tasar\u0131m\u0131<\/li>\n<li>YSA Nas\u0131l \u00d6\u011frenir ? : Perceptron (Alg\u0131lay\u0131c\u0131) kavram\u0131<\/li>\n<li>Gradyan Al\u00e7al\u0131\u015f (Gradient Descendent)<\/li>\n<li>Y\u0131\u011f\u0131n (Batch), \u00a0Stokastik (stochasftic) ve Mini Y\u0131\u011f\u0131n (mini Batch) gradyan al\u00e7al\u0131\u015f (gradient Descendent)<\/li>\n<li>\u0130leri yay\u0131l\u0131m\u0131n (forward propagation) ve geri yay\u0131l\u0131ml\u0131 (backward propagation) a\u011flar<\/li>\n<li>Derin \u00d6\u011frenme K\u00fct\u00fcphaneleri ve kar\u015f\u0131la\u015ft\u0131rma\n<ul>\n<li>Keras, Caffe, TensorFlow, DeepLearning4J ve PyTorch kar\u015f\u0131la\u015ft\u0131rmas\u0131\n<ul>\n<li>Keras:\u00a0<a href=\"https:\/\/keras.io\/\">https:\/\/keras.io<\/a><\/li>\n<li>TensorFlow:\u00a0<a href=\"https:\/\/www.tensorflow.org\/\">https:\/\/www.tensorflow.org<\/a><\/li>\n<li>Caffe :\u00a0<a href=\"http:\/\/caffe.berkeleyvision.org\/\">http:\/\/caffe.berkeleyvision.org<\/a><\/li>\n<li>DeepLearning4J :\u00a0<a href=\"https:\/\/deeplearning4j.org\/\">https:\/\/deeplearning4j.org<\/a><\/li>\n<li>PyTorch :\u00a0<a href=\"https:\/\/pytorch.org\/\">https:\/\/pytorch.org<\/a><\/li>\n<\/ul>\n<\/li>\n<\/ul>\n<\/li>\n<li>Derin \u00d6\u011frenme K\u00fct\u00fcphanelerinin kurulmas\u0131\n<ul>\n<li>Theano :\u00a0pip install \u2013upgrade \u2013no-deps git+git:\/\/github.com\/Theano\/Theano.git<\/li>\n<li>TensorFlow:\u00a0conda create -n tensorflow python=3.5<\/li>\n<li>Keras :\u00a0pip install \u2013upgrade keras<\/li>\n<li>TensorFlow:\u00a0pip3 install \u2013upgrade https:\/\/storage.googleapis.com\/tensorflow\/mac\/cpu\/tensorflow-1.8.0-py3-none-any.whl<\/li>\n<\/ul>\n<\/li>\n<li>Veri K\u00fcmesi ve Problemin Tan\u0131t\u0131m\u0131\n<ul>\n<li><a href=\"http:\/\/www.bilkav.com\/wp-content\/uploads\/2018\/03\/Churn_Modelling.csv\">Veri K\u00fcmesini indirmek i\u00e7in t\u0131klay\u0131n\u0131z.<\/a><\/li>\n<\/ul>\n<\/li>\n<li>Python ile kodlama\n<ul>\n<li><a href=\"http:\/\/www.bilkav.com\/wp-content\/uploads\/2018\/03\/ann.py_.zip\">Python kodunu indirmek i\u00e7in t\u0131klay\u0131n\u0131z.<\/a><\/li>\n<\/ul>\n<\/li>\n<\/ul>\n<\/li>\n<\/ul>\n<\/li>\n<\/ul>\n<p><iframe loading=\"lazy\" title=\"Python - Django E\u011fitimleri 1 : Giri\u015f\" width=\"960\" height=\"540\" src=\"https:\/\/www.youtube.com\/embed\/l1EQ2GfxmUg?list=PLh9ECzBB8tJMkq3vJ8fwAKNlwPA8d629n\" frameborder=\"0\" allow=\"accelerometer; autoplay; clipboard-write; encrypted-media; gyroscope; picture-in-picture; web-share\" referrerpolicy=\"strict-origin-when-cross-origin\" allowfullscreen><\/iframe><\/p>\n<p><strong>Duyurular:<\/strong><\/p>\n<p>Proje duyurusu:<\/p>\n<p>Veri odakl\u0131 programlama dersi proje duyurusu (minimum olmas\u0131 gerekenler)<\/p>\n<ol>\n<li>Proje \u00f6nerisi en ge\u00e7 1 Aral\u0131\u011fa kadar yollanacak : K\u0131sa problem tan\u0131m\u0131 ve veri tan\u0131m\u0131 (nas\u0131l eri\u015filece\u011fi ve verinin detaylar\u0131):\n<ol>\n<li>hangi tarihte sunum istendi\u011fi belirtilecek (15 aral\u0131k veya 22 aral\u0131k veya fark etmez)<\/li>\n<li>Projeler tek ki\u015fi olacak, kendi problemleriniz (\u00e7al\u0131\u015ft\u0131\u011f\u0131n\u0131z yer ile ilgili olmas\u0131 tercih sebebidir). \u015eayet olmuyorsa kaggle.com\u2019dan problem se\u00e7ip \u00f6nerilebilir.<\/li>\n<\/ol>\n<\/li>\n<li>Teslim edilecekler (teslim i\u00e7in 14 Aral\u0131k son tarih) : 1Proje raporu + 2 Sunum + 3 \u00c7al\u0131\u015fan kod (CRISP-DM metodolojisi kullan\u0131lacak)<\/li>\n<li>Sunum (10 + 5 dakika) : problemin tan\u0131m\u0131, \u00e7\u00f6z\u00fcm\u00fcn faydalar\u0131, kodun demosu (\u00e7al\u0131\u015ft\u0131r\u0131lmas\u0131)<\/li>\n<li>Sunumlar tarihi :15 ve 22 Aral\u0131k olacak (isteklere \u00f6ncelik verilecek)<\/li>\n<\/ol>\n","protected":false},"excerpt":{"rendered":"<p>T. C. \u0130stanbul \u015eehir \u00dcniversitesi \u0130\u015f Analiti\u011fi Y\u00fcksek Lisans Dersi Ders izlencesi ve ders ile ilgili faydal\u0131 i\u00e7erik Dersin Ad\u0131: Veri Odakl\u0131 Programlama, Python ile Dersin Kodu: IAN 502 D\u00f6nemi: G\u00fcz 2018 Kredisi : 3 \u00d6\u011fretim \u00dcyesi: Do\u00e7. Dr. \u015eadi Evren \u015eEKER \u0130leti\u015fim: python2018@sadievrenseker.com Ders \u0130\u00e7eri\u011fi: Veri odakl\u0131 programlama dersinin 3 farkl\u0131 seviyeden \u00f6\u011frencilere hitap etmesi beklenmektedir. Hen\u00fcz programlama ile &hellip; <a href=\"https:\/\/sadievrenseker.com\/?p=2124\">Continue Reading <span class=\"meta-nav\">&rarr;<\/span><\/a><\/p>\n","protected":false},"author":1,"featured_media":0,"comment_status":"closed","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[1],"tags":[],"class_list":["post-2124","post","type-post","status-publish","format-standard","hentry","category-uncategorized"],"_links":{"self":[{"href":"https:\/\/sadievrenseker.com\/index.php?rest_route=\/wp\/v2\/posts\/2124","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/sadievrenseker.com\/index.php?rest_route=\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/sadievrenseker.com\/index.php?rest_route=\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/sadievrenseker.com\/index.php?rest_route=\/wp\/v2\/users\/1"}],"replies":[{"embeddable":true,"href":"https:\/\/sadievrenseker.com\/index.php?rest_route=%2Fwp%2Fv2%2Fcomments&post=2124"}],"version-history":[{"count":6,"href":"https:\/\/sadievrenseker.com\/index.php?rest_route=\/wp\/v2\/posts\/2124\/revisions"}],"predecessor-version":[{"id":2143,"href":"https:\/\/sadievrenseker.com\/index.php?rest_route=\/wp\/v2\/posts\/2124\/revisions\/2143"}],"wp:attachment":[{"href":"https:\/\/sadievrenseker.com\/index.php?rest_route=%2Fwp%2Fv2%2Fmedia&parent=2124"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/sadievrenseker.com\/index.php?rest_route=%2Fwp%2Fv2%2Fcategories&post=2124"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/sadievrenseker.com\/index.php?rest_route=%2Fwp%2Fv2%2Ftags&post=2124"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}