16+ Saat Python ile Veri Bilimi ve Makine renmesi [2020] | Software Engineering Online Course by Udemy

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Akademik seviyede Veri bilimi ve Makine renmesi’nin (Machine Learning) yaln bir ekilde anlatld kurs.

An excellent training about Software Engineering

16+ Saat Python ile Veri Bilimi ve Makine renmesi [2020]

Herkese Merhabalar, Makine renmesi ve Yapay Zeka algoritmalar artk hemen her alanda yaygn olarak kullanlyor. Veri bilimi ile alakal en byk problem bu dala ynelmek isteyen insanlarn yeterli istatistik ve lineer cebir bilgisi olmadan sadece kod yazarak ilerlemeye almasdr. Bu kursta teorik ve matematiksel tarafn mhendislik, istatistik ya da ekonometri bile olabilir, bu dallara yakn olan herkes iin yaln biimde anlatldn ve uygulamalarla desteklendiini greceksiniz. Kurs ierii;- Introduction to Machine LearningWhat is Machine Learning? (Makine renmesi Nedir? ) Statistics for Machine Learning (Makine renmesi iin statistik) Linear Algebra for Machine Learning (Makine renmesi iin Lineer Cebir) Data Pre-Processing (Veri n leme) Exploratory Data Analysis (Keifsel Veri Analizi) – Supervised LearningClassification (Snflama) K Nearest Neighbors Regression (K Yakn Komu – Regresyon) Performance Evaluation Metrics (Performans Deerleme Metrikleri) Naive Bayes Classifier (Naive Bayes Snflaycs) Logistic Regression (Lojistik Regression) Support Vector Machines (Destek Vektr Makineleri) Decision Trees (Karar aalar) Decision Tree Regression (Karar Aac Regresyonu)Random Forest Regression (Rasgele Ormanlar ve Regresyonu) Ensemble Learning (Kollektif renme) Adaboost Gradient Boost XGBoost Introduction to Neural Networks (Yapay Sinir Alarna Giri) Multi-Layer Perceptron (ok katmanl YSAlar) Backpropagation (Geri Yaylml Optimizasyon) – Unsupervised LearningIntroduction to Clustering (Kmelemeye Giri) K-Means Clustering (K-Ortalama Kmeleme) Hierarchical Clustering (Hiyerarik Kmeleme) Principal Component Analysis (Temel Bileenler Analizi) – Association Rules Mining (Birliktelik Kural karm) – Zaman Serileri Analizi ve ARIMA Modelleri

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