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   001 Introduction to Predictive Modelling with Python.en.srt

   002 Installation.en.srt

   001 Data Preprocessing.en.srt

   002 Dataframe.en.srt

   003 Imputer.en.srt

   004 Create Dumies.en.srt

   005 Splitting Dataset.en.srt

   006 Features Scaling.en.srt

   001 Introduction to Linear Regression.en.srt

   002 Estimated Regression Model.en.srt

   003 Import the Library.en.srt

   004 Plot.en.srt

   005 Tip Example.en.srt

   006 Print Function.en.srt

   001 Introduction to Salary Dataset.en.srt

   002 Fitting Linear Regression.en.srt

   003 Fitting Linear Regression Continue.en.srt

   004 Prediction from the Model.en.srt

   005 Prediction from the Model Continue.mp4

   001 Introduction to Multiple Linear Regression.en.srt

   002 Creating Dummies.en.srt

   003 Removing one Dummy and Splitting Dataset.en.srt

   004 Training Set and Predictions.en.srt

   005 Stats Models to Make Optimal Model.en.srt

   006 Steps to Make Optimal Model.en.srt

   007 Making Optimal Model by Backward Elimination.en.srt

   008 Adjusted R Square.en.srt

   009 Final Optimal Model Implementation.en.srt

   001 Introduction to Jupyter Notebook.en.srt

   002 Understanding Dataset and Problem Statement.en.srt

   003 Working with Correlation Plots.en.srt

   004 Working with Correlation Plots Continue.en.srt

   005 Correlation Plot and Splitting Dataset.en.srt

   006 MLR Model with Sklearn and Predictions.en.srt

   007 MLR model with Statsmodels and Predictions.en.srt

   008 Getting Optimal model with Backward Elimination Approach.en.srt

   009 RMSE Calculation and Multicollinearity Theory.en.srt

   010 VIF Calculation.en.srt

   011 VIF and Correlation Plots.en.srt

   011 VIF and Correlation Plots.mp4.vtx

   001 Introduction to Logistic Regression.en.srt

   002 Understanding Problem Statement and Splitting.mp4

   003 Scaling and Fitting Logistic Regression Model.mp4

   004 Prediction and Introduction to Confusion Matrix.mp4

   005 Confusion Matrix Explanation.mp4

   006 Checking Model Performance using Confusion Matrix.mp4

   007 Plots Understanding.mp4

   008 Plots Understanding Continue.mp4

   001 Introduction and data Preprocessing.en.srt

   002 Fitting Model with Sklearn Library.en.srt

   003 Fitting Model with Statmodel Library.en.srt

   004 Using Statsmodel Package.en.srt

   005 Backward Elimination Approach.en.srt

   006 Backward Elimination Approach Continue.en.srt

   007 More on Backward Elimination Approach.en.srt

   008 Final Model.en.srt

   009 ROC Curves.en.srt

   010 Threshold Changing.en.srt

   011 Final Predictions.en.srt

   001 Intro to Credit Risk.en.srt

   002 Label Encoding.en.srt

   003 Gender Variable.en.srt

   004 Dependents and Education Variable.en.srt

   005 Missing Values Treatment in Self Employed Variable.en.srt

   006 Outliers Treatment in Applicant Income Variable.en.srt

   007 Missing Values.en.srt

   008 Property Area Variable.en.srt

   009 Splitting Data.en.srt

   010 Final Model and Area under ROC Curve.en.srt