Udemy - Data Science in R: Be an Expert in Regression Analysis in R [Giga Course]

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01 Introduction to the course, Machine Learning & Regression Analysis
  • 001 Introduction.mp4 (21.4 MB)
  • 002 Introduction to Regression Analysis.mp4 (49.1 MB)
  • 003 What is Machine Leraning and it's main types_.mp4 (34.3 MB)
  • 004 Overview of Machine Leraning in R.mp4 (5.7 MB)
02 Software used in this course R-Studio and Introduction to R
  • 001 Introduction to Section 2.mp4 (3.8 MB)
  • 002 What is R and RStudio_.mp4 (12.2 MB)
  • 003 How to install R and RStudio in 2020.mp4 (16.7 MB)
  • 004 Lab_ Install R and RStudio in 2020.mp4 (38.7 MB)
  • 005 Introduction to RStudio Interface.mp4 (30.7 MB)
  • 006 Lab_ Get started with R in RStudio.mp4 (47.7 MB)
03 R Crash Course - get started with R-programming in R-Studio
  • 001 Introduction to Section 3.mp4 (4.0 MB)
  • 002 Lab_ Installing Packages and Package Management in R.mp4 (24.1 MB)
  • 003 Variables in R and assigning Variables in R.mp4 (9.0 MB)
  • 004 Lab_ Variables in R and assigning Variables in R.mp4 (7.6 MB)
  • 005 Overview of data types and data structures in R.mp4 (27.2 MB)
  • 006 Lab_ data types and data structures in R.mp4 (48.1 MB)
  • 007 Vectors' operations in R.mp4 (35.9 MB)
  • 008 Data types and data structures_ Factors.mp4 (9.3 MB)
  • 009 Dataframes_ overview.mp4 (16.7 MB)
  • 010 Functions in R - overview.mp4 (24.8 MB)
  • 011 Lab_ For Loops in R.mp4 (24.8 MB)
  • 011 R Crash Course I_udemy_script.R (12.9 KB)
  • 012 Read Data into R.mp4 (31.9 MB)
04 Linear Regression Analysis for Supervised Machine Learning in R
  • 001 Overview of Regression Analysis.mp4 (49.2 MB)
  • 002 Graphical Analysis of Regression Models.mp4 (16.1 MB)
  • 003 Your first linear regression model in R.mp4 (53.3 MB)
  • 004 Lab_ Correlation & Linear Regression Analysis in R.mp4 (13.1 MB)
  • 005 How to know if the model is best fit for your data - theory.mp4 (9.1 MB)
  • 006 Lab_ Linear Regression Diagnostics.mp4 (43.2 MB)
  • 007 Lab how to measure the linear model's fit_ AIC and BIC.mp4 (8.6 MB)
  • 008 Evaluation of Prediction Model Performance in Supervised Learning_ Regression.mp4 (6.7 MB)
  • 009 Predict with linear regression model & RMSE as in-sample error.mp4 (24.4 MB)
  • 010 Prediction model evaluation with data split_ out-of-sample RMSE.mp4 (31.2 MB)
  • 025 018_LM_diamonds.R (2.2 KB)
  • 026 020_CorrelationLinear.R (0.8 KB)
  • 028 020_LM_Diagnosis.R (1.4 KB)
  • 029 021_AIC.R (0.5 KB)
  • 031 019_RMSE_LM.R (0.8 KB)
  • 032 022_RegressionModelValidation.R (0.9 KB)
  • [GigaCourse.Com].url (0.0 KB)
05 More types of regression models
  • 001 Lab_ Multiple linear regression - model estimation.mp4 (60.1 MB)
  • 002 Lab_ Multiple linear regression - prediction.mp4 (18.8 MB)
  • 003 Lab_ Multiple linear regression with interaction.mp4 (44.5 MB)
  • 004 Regression with Categorical Variables_ Dummy Coding Essentials in R.mp4 (29.7 MB)
  • 005 ANOVA - Categorical variables with more than two levels in linear regressions.mp4 (54.5 MB)
  • 033 029_MultipleLinearRegression.R (3.8 KB)
  • 035 030_MultipleLinearRegression_interactions.R (1.5 KB)
  • 036 031_DummyVariables.R (1.1 KB)
  • 037 032_ANOVA.R (1.2 KB)
06 Non-Linear Regression Analysis in R_ Polynomial & Spline regression, GAMs
  • 001 Nonlinear Regression Essentials in R_ Polynomial and Spline Regression Models.mp4 (26.0 MB)
  • 002 Lab_ Polynomial regression in R.mp4 (64.9 MB)
  • 003 Lab_ Log transformation in R.mp4 (19.0 MB)
  • 004 Lab_ Spline regression in R.mp4 (47.0 MB)
  • 005 Lab_ Generalized additive models in R.mp4 (47.5 MB)
  • 039 033_PolynomialRegression.R (2.0 KB)
  • 040 034_PolyRegression_LogTransform.R (2.7 KB)
  • 041 035_SplineRegression.R (2.3 KB)
  • 042 036_GAM.R (0.4 KB)
07 Non-Parametric Regression Analysis in R_ Random Forest, Decision Trees and more
  • 001 Classification and Decision Trees (CART)_ Theory.mp4 (13.3 MB)
  • 002 Lab_ Decision Trees in R.mp4 (52.0 MB)
  • 003 Random Forest_ Theory.mp4 (21.3 MB)
  • 004 Lab_ Random Forest in R.mp4 (100.1 MB)
  • 005 Lab_ Machine Learning Models' Comparison & Best Model Selection.mp4 (101.2 MB)
  • 006 Your Final Project.mp4 (15.0 MB)
  • 044 025_DecisionTress.R (1.2 KB)
  • 046 026_RandomForest.R (1.8 KB)
  • 047 027_ModelCompare.R (3.1 KB)
  • [GigaCourse.Com].url (0.0 KB)

Description

Udemy - Data Science in R: Be an Expert in Regression Analysis in R [Giga Course]

Learn Complete Hands-On Regression Analysis in R for Machine Learning, Statistical Analysis, Data Science, Deep Learning

Created by Kate Alison, Georg Müller
Last updated 1/2021
English
English [Auto]

For More Udemy Courses Visit: https://gigacourse.com



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Udemy - Data Science in R: Be an Expert in Regression Analysis in R [Giga Course]

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Udemy - Data Science in R: Be an Expert in Regression Analysis in R [Giga Course]

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