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   001 Course Structure & Outline.en.srt

   002 READ ME_ Important Notes for New Students.html

   003 About This Series.mp4

   004 Machine Learning Part 3 - Regression.pdf

   005 Setting Expectations.en.srt

   001 Supervised vs. Unsupervised Learning.en.srt

   002 RECAP_ Key Concepts.en.srt

   003 Regression 101.en.srt

   004 Regression Workflow.en.srt

   005 Feature Engineering.en.srt

   006 Splitting & Overfitting.en.srt

   007 Prediction vs. Root-Cause Analysis.en.srt

   001 Intro to Regression Modeling.en.srt

   002 Linear Relationships.en.srt

   003 Least Squared Error.en.srt

   004 Univariate Linear Regression.en.srt

   005 CASE STUDY_ Univariate Linear Regression.en.srt

   006 Multiple Linear Regression.en.srt

   007 Non-Linear Regression.en.srt

   008 CASE STUDY_ Non-Linear Regression.en.srt

   001 Intro to Model Diagnostics.en.srt

   002 Sample Model Output.en.srt

   003 R-Squared.en.srt

   004 Mean Error Metrics (MSE, MAE, MAPE).en.srt

   005 Homoskedasticity.en.srt

   006 Null Hypothesis.en.srt

   007 F-Significance.en.srt

   008 T-Values & P-Values.en.srt

   009 Multicollinearity.en.srt

   010 Variance Inflation Factor.en.srt

   011 RECAP_ Sample Model Output.en.srt

   001 Intro to Forecasting.en.srt

   002 Seasonality.en.srt

   003 Auto Correlation Function.en.srt

   004 CASE STUDY_ Seasonality with ACF.en.srt

   005 One-Hot Encoding.en.srt

   006 CASE STUDY_ Seasonality with One-Hot Encoding.en.srt

   007 Linear Trending.en.srt

   008 CASE STUDY_ Seasonality with Linear Trend.en.srt

   009 Smoothing.en.srt

   010 CASE STUDY_ Smoothing.en.srt

   011 Non-Linear Trends.en.srt

   012 CASE STUDY_ Non-Linear Trend.en.srt

   013 Intervention Analysis.en.srt

   014 CASE STUDY_ Intervention Analysis.en.srt

   001 Looking Ahead to Part 4.en.srt

   002 BONUS LECTURE.html

  Bonus Resources.txt