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Regression Analysis for Business Managers in Python and R
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[TutsNode.com] - Regression Analysis for Business Managers in Python and R (Size: 2.19 GB) (Files: 248)
[TutsNode.com] - Regression Analysis for Business Managers in Python and R
04 Linear Regression - R
015 How much would my apartment cost_.mp4
008 Scatterplotting.en.srt
015 How much would my apartment cost_.en.srt
001 Loading data.en.srt
006 Transforming variable into numeric advanced.en.srt
002 Handpicking variables.en.srt
005 Transforming variable into numeric.en.srt
009 Removing outliers.en.srt
014 Regression summary.en.srt
007 Summary statistics.en.srt
012 Log transforming variables.en.srt
010 Correlation Matrix.en.srt
004 Transforming variables into factors.en.srt
006 Transforming variable into numeric advanced.mp4
003 Dataset strategy.en.srt
013 Linear Regression.en.srt
011 Dropping variables.en.srt
008 Scatterplotting.mp4
005 Transforming variable into numeric.mp4
001 Loading data.mp4
009 Removing outliers.mp4
010 Correlation Matrix.mp4
002 Handpicking variables.mp4
007 Summary statistics.mp4
014 Regression summary.mp4
012 Log transforming variables.mp4
004 Transforming variables into factors.mp4
003 Dataset strategy.mp4
013 Linear Regression.mp4
011 Dropping variables.mp4
01 Introduction
001 Introduction.en.srt
004 Reviews and future of this course.en.srt
005 Let's connect!.html
002 Installing Python and Spyder.en.srt
003 Installing R and RStudio.en.srt
004 Reviews and future of this course.mp4
002 Installing Python and Spyder.mp4
003 Installing R and RStudio.mp4
001 Introduction.mp4
02 Linear Regression - Intuition
003 Pricing demand factors.en.srt
004 Supply demand factors.en.srt
007 How to read coefficients.en.srt
009 (Adjusted) R-squared.en.srt
012 Linear regression step by step guide.en.srt
001 Linear Regression objectives.en.srt
013 Case study briefing.en.srt
008 Dummy variable trap.en.srt
010 RSME vs MAE.en.srt
006 Linear Regression summary.en.srt
005 Linear Regression.en.srt
002 What influences pricing.en.srt
011 Outliers.en.srt
018 Regression Analysis for Business Managers in Python and R templates.zip
008 Dummy variable trap.mp4
007 How to read coefficients.mp4
006 Linear Regression summary.mp4
003 Pricing demand factors.mp4
010 RSME vs MAE.mp4
005 Linear Regression.mp4
004 Supply demand factors.mp4
013 Case study briefing.mp4
009 (Adjusted) R-squared.mp4
001 Linear Regression objectives.mp4
011 Outliers.mp4
002 What influences pricing.mp4
012 Linear regression step by step guide.mp4
05 Logistic Regression - Intuition
002 Understanding Churn.en.srt
007 Confusion Matrix.en.srt
006 Over vs underfitting & Bias Variance trade off.en.srt
003 Preventing Churn.en.srt
004 Logistic Regression.en.srt
001 Logistic Regression Objectives.en.srt
005 Training and test set.en.srt
009 Case study briefing.en.srt
008 Logistic Regression - step by step guide.en.srt
056 Regression Analysis for Business Managers in Python and R templates.zip
007 Confusion Matrix.mp4
002 Understanding Churn.mp4
004 Logistic Regression.mp4
009 Case study briefing.mp4
006 Over vs underfitting & Bias Variance trade off.mp4
003 Preventing Churn.mp4
001 Logistic Regression Objectives.mp4
005 Training and test set.mp4
008 Logistic Regression - step by step guide.mp4
07 Logistic Regression - R
005 Outlier detection.en.srt
010 Logistic Regression.en.srt
006 Removing outliers.en.srt
001 Loading libraries and dataset.en.srt
012 Confusion Matrix.en.srt
004 Summary statistics.en.srt
011 Predictions.en.srt
009 Training and test set.en.srt
002 Data structure.en.srt
003 Transforming objects into factors.en.srt
008 Correlation Matrix.en.srt
007 Transforming variable into its logarithm.en.srt
005 Outlier detection.mp4
006 Removing outliers.mp4
004 Summary statistics.mp4
012 Confusion Matrix.mp4
010 Logistic Regression.mp4
001 Loading libraries and dataset.mp4
009 Training and test set.mp4
011 Predictions.mp4
008 Correlation Matrix.mp4
003 Transforming objects into factors.mp4
002 Data structure.mp4
007 Transforming variable into its logarithm.mp4
03 Linear Regression - Python
001 Importing libraries and dataset.en.srt
008 Removing outliers.en.srt
005 Transforming the dependent variable.en.srt
013 Linear regression.en.srt
011 Log transforming variables.en.srt
003 Transforming objects into dummy variables.en.srt
007 Scatterplotting.en.srt
002 Handpicking variables.en.srt
006 Summary statistics.en.srt
004 Transforming the _floor_ variable into numeric.en.srt
009 Correlation Matrix.en.srt
010 Dropping variables.en.srt
014 How much would my apartment cost_.en.srt
012 Isolate X and Y variables.en.srt
008 Removing outliers.mp4
013 Linear regression.mp4
007 Scatterplotting.mp4
005 Transforming the dependent variable.mp4
006 Summary statistics.mp4
011 Log transforming variables.mp4
001 Importing libraries and dataset.mp4
004 Transforming the _floor_ variable into numeric.mp4
003 Transforming objects into dummy variables.mp4
002 Handpicking variables.mp4
009 Correlation Matrix.mp4
014 How much would my apartment cost_.mp4
012 Isolate X and Y variables.mp4
010 Dropping variables.mp4
06 Logistic Regression - Python
012 Logistic Regression.en.srt
002 Data structure.en.srt
014 Confusion Matrix.en.srt
004 Summary statistics.en.srt
001 Importing libraries and dataset.en.srt
011 Training and test set.en.srt
005 Outlier detection.en.srt
013 Predictions.en.srt
008 Correlation Matrix.en.srt
006 Removing outliers.en.srt
003 Transforming objects into dummy variables.en.srt
009 Isolating X and Y variables.en.srt
007 Transforming variable into its logarithm.en.srt
010 Logistic regression preparation.en.srt
012 Logistic Regression.mp4
002 Data structure.mp4
004 Summary statistics.mp4
011 Training and test set.mp4
005 Outlier detection.mp4
014 Confusion Matrix.mp4
001 Importing libraries and dataset.mp4
013 Predictions.mp4
008 Correlation Matrix.mp4
006 Removing outliers.mp4
009 Isolating X and Y variables.mp4
003 Transforming objects into dummy variables.mp4
010 Logistic regression preparation.mp4
007 Transforming variable into its logarithm.mp4
08 Bonus lecture
001 ___Last Lecture.html
TutsNode.com.txt
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