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In this course you will learn how to do simple linear Regression Analysis using R.

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Course Curriculum

Regression Analysis: Simple Linear Regression Using R 00:00:00
Linear Regression in R 00:00:00
Multicollinearity 00:00:00
Treating Multicollinearity in R 00:00:00
Logistic Regression Using R 00:00:00
Missing Values Treatment in R 00:00:00
Outlier Detection & Treatment in R 00:00:00
Cluster Analysis – K Means Clustering in R 00:00:00
Association Rule Mining in R 00:00:00
Measuring Performance of Predictive Models 00:00:00
Logistic Regression Model for Stock Price Movement 00:00:00
Decision Tree Model for Regression Problem in R 00:00:00
Decision Tree Vs. Linear Regression 00:00:00
Bagging & Ensemble Models – Bootstrap aggregation 00:00:00
Random Forest Model Theory & Application using R 00:00:00
Quadratic Discriminant Analysis 00:00:00
Multinomial Logistic Regression in R 00:00:00
Negative Binomial Regression Model 00:00:00
Cross Validation For Model Selection 00:00:00
Bootstrapping: Evaluating Model Statistics using Re-sampling 00:00:00
Feature Selection in Machine Learning 00:00:00
Principal Component Regression 00:00:00
Partial Least Square Regression (PLS) 00:00:00
Statistical & Data Science Modelling in High Dimension 00:00:00
Which is Better – Regression or Tree Based Model? 00:00:00
Spline Regression 00:00:00

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