DesireCourse Net Udemy Credit Risk Modeling in Python 2020

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/1. Introduction/

1. What does the course cover.mp4

1. What does the course cover.srt

10. Different facility types (asset classes) and credit risk modeling approaches.mp4

10. Different facility types (asset classes) and credit risk modeling approaches.srt

11. Different facility types (asset classes) and credit risk modeling approaches.html

2. What is credit risk and why is it important.mp4

2. What is credit risk and why is it important.srt

3. What is credit risk and why is it important.html

4. Expected loss (EL) and its components PD, LGD and EAD.mp4

4. Expected loss (EL) and its components PD, LGD and EAD.srt

5. Expected loss (EL) and its components PD, LGD and EAD.html

6. Capital adequacy, regulations, and the Basel II accord.mp4

6. Capital adequacy, regulations, and the Basel II accord.srt

7. Capital adequacy, regulations, and the Basel II accord.html

8. Basel II approaches SA, F-IRB, and A-IRB.mp4

8. Basel II approaches SA, F-IRB, and A-IRB.srt

9. Basel II approaches SA, F-IRB, and A-IRB.html

/10. LGD and EAD Models Preparing the data/

1. LGD and EAD models independent variables..mp4

1. LGD and EAD models independent variables..srt

1.1 loan_data_2007_2014_preprocessed.csv.html

1.2 LGD and EAD models independent variables..html

1.3 LGD and EAD models independent variables with comments.html

2. LGD and EAD models independent variables.html

3. LGD and EAD models dependent variables.mp4

3. LGD and EAD models dependent variables.srt

3.1 LGD and EAD models dependent variables.html

3.2 LGD and EAD models dependent variables with comments.html

4. LGD and EAD models dependent variables.html

5. LGD and EAD models distribution of recovery rates and credit conversion factors.mp4

5. LGD and EAD models distribution of recovery rates and credit conversion factors.srt

5.1 LGD and EAD models distribution of recovery rates and credit conversion factors.html

5.2 LGD and EAD models distribution of recovery rates and credit conversion factors with comments.html

6. LGD and EAD models distribution of recovery rates and credit conversion factors.html

/11. LGD model/

1. LGD model preparing the inputs.mp4

1. LGD model preparing the inputs.srt

1.1 loan_data_2007_2014_preprocessed.csv.html

1.2 LGD model preparing the inputs with comments.html

1.3 LGD model preparing the inputs.html

10. LGD model combining stage 1 and stage 2.mp4

10. LGD model combining stage 1 and stage 2.srt

10.1 LGD model combining stage 1 and stage 2.html

10.2 LGD model combining stage 1 and stage 2 with comments.html

11. LGD model combining stage 1 and stage 2.html

12. Homework building an updated LGD model.html

12.1 Dataset with new data (loan_data_2015.csv).html

2. LGD model testing the model.mp4

2. LGD model testing the model.srt

2.1 LGD model testing the model with comments.html

2.2 LGD model testing the model.html

3. LGD model testing the model.html

4. LGD model estimating the accuracy of the model.mp4

4. LGD model estimating the accuracy of the model.srt

4.1 LGD model estimating the accuracy of the model with comments.html

4.2 LGD model estimating the accuracy of the model.html

5. LGD model saving the model.mp4

5. LGD model saving the model.srt

5.1 LGD model saving the model with comments.html

5.2 LGD model saving the model.html

6. LGD model stage 2 – linear regression.mp4

6. LGD model stage 2 – linear regression.srt

6.1 LGD model stage 2 – linear regression.html

6.2 LGD model stage 2 – linear regression with comments.html

7. LGD model stage 2 – linear regression with comments.html

8. LGD model stage 2 – linear regression evaluation.mp4

8. LGD model stage 2 – linear regression evaluation.srt

8.1 LGD model stage 2 – linear regression evaluation with comments.html

8.2 LGD model stage 2 – linear regression evaluation.html

9. LGD model stage 2 – linear regression evaluation.html

/12. EAD model/

1. EAD model estimation and interpretation.mp4

1. EAD model estimation and interpretation.srt

1.1 EAD model estimation and interpretation with comments.html

1.2 EAD model estimation and interpretation.html

2. EAD model estimation and interpretation.html

3. EAD model validation.mp4

3. EAD model validation.srt

3.1 EAD model validation with comments.html

3.2 EAD model validation.html

4. EAD model validation.html

5. Homework building an updated EAD model.html

/13. Calculating expected loss/

1. Calculating expected loss.mp4

1. Calculating expected loss.srt

1.1 Calculating expected loss with comments.html

1.2 Calculating expected loss.html

2. Calculating expected loss.html

3. Homework calculate expected loss on more recent data.html

3.1 Calculating expected loss complete notebook.html

3.2 Calculating expected loss complete notebook with comments.html

/2. Setting up the working environment/

1. Setting up the environment - Do not skip, please!.mp4

1. Setting up the environment - Do not skip, please!.srt

2. Why Python and why Jupyter.mp4

2. Why Python and why Jupyter.srt

3. Installing Anaconda.mp4

3. Installing Anaconda.srt

4. Jupyter Dashboard - Part 1.mp4

4. Jupyter Dashboard - Part 1.srt

5. Jupyter Dashboard - Part 2.mp4

5. Jupyter Dashboard - Part 2.srt

5.1 Shortcuts-for-Jupyter.pdf

6. Installing the sklearn package.mp4

6. Installing the sklearn package.srt

/3. Dataset description/

1. Our example consumer loans. A first look at the dataset.mp4

1. Our example consumer loans. A first look at the dataset.srt

1.1 LCDataDictionary.xlsx

1.2 Data Preparation.html

1.3 Data preparation with comments.html

1.4 Dataset for the course.html

2. Our example consumer loans. A first look at the dataset.html

3. Dependent variables and independent variables.mp4

3. Dependent variables and independent variables.srt

3.1 Dataset for the course.html

4. Dependent variables and independent variables.html

/4. General preprocessing/

1. Importing the data into Python.mp4

1. Importing the data into Python.srt

1.1 Importing the data into Python with comments.html

1.2 Importing the data into Python.html

10. Check for missing values and clean Homework.html

10.1 Check for missing values and clean the data Homework - Solution with comments.html

10.2 Check for missing values and clean the data Homework - Solution.html

2. Importing the data into Python.html

3. Preprocessing few continuous variables.mp4

3. Preprocessing few continuous variables.srt

3.1 Preprocessing few continuous variables.html

3.2 Preprocessing few continuous variables with comments.html

4. Preprocessing few continuous variables.html

5. Preprocessing few continuous variables Homework.html

5.1 Preprocessing few continuous variables Homework - Solution with comments.html

5.2 Preprocessing few continuous variables Homework - Solution.html

6. Preprocessing few discrete variables.mp4

6. Preprocessing few discrete variables.srt

6.1 Preprocessing few discrete variables with comments.html

6.2 Preprocessing few discrete variables.html

7. Preprocessing few discrete variables.html

8. Check for missing values and clean.mp4

8. Check for missing values and clean.srt

8.1 Check for missing values and clean.html

8.2 Check for missing values and clean with comments.html

9. Check for missing values and clean.html

/5. PD Model Data Preparation/

1. How is the PD model going to look like.mp4

1. How is the PD model going to look like.srt

10. Data preparation. Splitting data.html

11. Data preparation. An example.mp4

11. Data preparation. An example.srt

11.1 Data preparation. An example with comments.html

11.2 Data preparation. An example.html

12. Data preparation. An example.html

13. Data preparation. Preprocessing discrete variables automating calculations.mp4

13. Data preparation. Preprocessing discrete variables automating calculations.srt

13.1 Data preparation. Preprocessing discrete variables automating calculations with comments.html

13.2 Data preparation. Preprocessing discrete variables automating calculations.html

14. Data preparation. Preprocessing discrete variables automating calculations.html

15. Data preparation. Preprocessing discrete variables visualizing results.mp4

15. Data preparation. Preprocessing discrete variables visualizing results.srt

15.1 Data preparation. Preprocessing discrete variables visualizing results with comments.html

15.2 Data preparation. Preprocessing discrete variables visualizing results.html

16. Data preparation. Preprocessing discrete variables creating dummies (Part 1).mp4

16. Data preparation. Preprocessing discrete variables creating dummies (Part 1).srt

16.1 Data preparation. Preprocessing discrete variables creating dummies (Part 1) with comments.html

16.2 Data preparation. Preprocessing discrete variables creating dummies (Part 1).html

17. Data preparation. Preprocessing discrete variables creating dummies (Part 1).html

18. Data preparation. Preprocessing discrete variables creating dummies (Part 2).mp4

18. Data preparation. Preprocessing discrete variables creating dummies (Part 2).srt

18.1 Data preparation. Preprocessing discrete variables creating dummies (Part 2) with comments.html

18.2 Data preparation. Preprocessing discrete variables creating dummies (Part 2).html

19. Data preparation. Preprocessing discrete variables creating dummies (Part 2).html

2. How is the PD model going to look like.html

20. Data preparation. Preprocessing discrete variables. Homework..html

20.1 Data preparation. Preprocessing discrete variables. Homework with comments.html

20.2 Data preparation. Preprocessing discrete variables Homework - Soluton.html

21. Data preparation. Preprocessing continuous variables Automating calculations.mp4

21. Data preparation. Preprocessing continuous variables Automating calculations.srt

21.1 Data preparation. Preprocessing continuous variables Automating calculations with comments.html

21.2 Data preparation. Preprocessing continuous variables Automating calculations.html

22. Data preparation. Preprocessing continuous variables Automating calculations.html

23. Data preparation. Preprocessing continuous variables creating dummies (Part 1).mp4

23. Data preparation. Preprocessing continuous variables creating dummies (Part 1).srt

23.1 Data preparation. Preprocessing continuous variables creating dummies (Part 1).html

23.2 Data preparation. Preprocessing continuous variables creating dummies (Part 1) with comments.html

24. Data preparation. Preprocessing continuous variables creating dummies (Part 1).html

25. Data preparation. Preprocessing continuous variables creating dummies (Part 2).mp4

25. Data preparation. Preprocessing continuous variables creating dummies (Part 2).srt

25.1 Data preparation. Preprocessing continuous variables creating dummies (Part 2).html

25.2 Data preparation. Preprocessing continuous variables creating dummies (Part 2) with comments.html

26. Data preparation. Preprocessing continuous variables creating dummies (Part 2).html

27. Data preparation. Preprocessing continuous variables creating dummies. Homework.html

27.1 Data preparation. Preprocessing continuous variables creating dummies. Homework.html

27.2 Data preparation. Preprocessing continuous variables creating dummies. Homework with comments.html

28. Data preparation. Preprocessing continuous variables creating dummies (Part 3).mp4

28. Data preparation. Preprocessing continuous variables creating dummies (Part 3).srt

28.1 Data preparation. Preprocessing continuous variables creating dummies (Part 3).html

28.2 Data preparation. Preprocessing continuous variables creating dummies (Part 3) with comments.html

29. Data preparation. Preprocessing continuous variables creating dummies (Part 3).html

3. Dependent variable Good Bad (default) definition.mp4

3. Dependent variable Good Bad (default) definition.srt

3.1 Dependent variable GoodBad with comments.html

3.2 Dependent variable GoodBad.html

30. Data preparation. Preprocessing continuous variables creating dummies. Homework.html

30.1 Data preparation. Preprocessing continuous variables creating dummies. Homework with comments.html

30.2 Data preparation. Preprocessing continuous variables creating dummies Homework - Solution.html

31. Data preparation. Preprocessing the test dataset.mp4

31. Data preparation. Preprocessing the test dataset.srt

31.1 Data preparation. Preprocessing the test dataset with comments.html

31.2 Data preparation. Preprocessing the test dataset.html

32. PD model data preparation notebooks.html

32.1 PD model data preparation with comments.html

32.2 PD model data preparation.html

4. Dependent variable Good Bad (default) definition.html

5. Fine classing, weight of evidence, and coarse classing.mp4

5. Fine classing, weight of evidence, and coarse classing.srt

6. Fine classing, weight of evidence, and coarse classing.html

7. Information value.mp4

7. Information value.srt

8. Information value.html

9. Data preparation. Splitting data.mp4

9. Data preparation. Splitting data.srt

9.1 Data preparation. Splitting data.html

9.2 Data preparation. Splitting data with comments.html

/6. PD model estimation/

1. The PD model. Logistic regression with dummy variables.mp4

1. The PD model. Logistic regression with dummy variables.srt

2. The PD model. Logistic regression with dummy variables.html

3. Loading the data and selecting the features.mp4

3. Loading the data and selecting the features.srt

3.1 Loading the data and selecting the features with comments.html

3.2 Loading the data and selecting the features.html

4. PD model estimation.mp4

4. PD model estimation.srt

4.1 PD model estimation with comments.html

4.2 PD model estimation.html

5. Build a logistic regression model with p-values.mp4

5. Build a logistic regression model with p-values.srt

5.1 Build a logistic regression model with p-values with comments.html

5.2 Build a logistic regression model with p-values.html

6. Build a logistic regression model with p-values.html

7. Interpreting the coefficients in the PD model.mp4

7. Interpreting the coefficients in the PD model.srt

8. Interpreting the coefficients in the PD model.html

/7. PD model validation/

1. Out-of-sample validation (test).mp4

1. Out-of-sample validation (test).srt

1.1 Out-of-sample validation (test).html

1.2 Out-of-sample validation (test) with comments.html

2. Out-of-sample validation (test).html

3. Evaluation of model performance accuracy and area under the curve (AUC).mp4

3. Evaluation of model performance accuracy and area under the curve (AUC).srt

3.1 Evaluation of model performance accuracy and area under the curve (AUC).html

3.2 Evaluation of model performance accuracy and area under the curve (AUC) with comments.html

4. Evaluation of model performance accuracy and area under the curve (AUC).html

5. Evaluation of model performance Gini and Kolmogorov-Smirnov.mp4

5. Evaluation of model performance Gini and Kolmogorov-Smirnov.srt

5.1 Evaluation of model performance Gini and Kolmogorov-Smirnov.html

5.2 Evaluation of model performance Gini and Kolmogorov-Smirnov with comments.html

6. Evaluation of model performance Gini and Kolmogorov-Smirnov.html

/8. Applying the PD Model for decision making/

1. Calculating probability of default for a single customer.mp4

1. Calculating probability of default for a single customer.srt

1.1 Calculating probability of default for a single customer with comments.html

1.2 Calculating probability of default for a single customer.html

10. Setting cut-offs. Homework.html

11. PD model logistic regression notebooks.html

11.1 PD model complete.html

11.2 PD model complete with comments.html

2. Creating a scorecard.mp4

2. Creating a scorecard.srt

2.1 Creating a scorecard.html

2.2 Creating a scorecard with comments.html

3. Creating a scorecard.html

4. Calculating credit score.mp4

4. Calculating credit score.srt

4.1 Calculating credit score.html

4.2 Calculating credit score with comments.html

5. Calculating credit score.html

6. From credit score to PD.mp4

6. From credit score to PD.srt

6.1 From credit score to PD.html

6.2 From credit score to PD with comments.html

7. From credit score to PD.html

8. Setting cut-offs.mp4

8. Setting cut-offs.srt

8.1 Setting cut-offs with comments.html

8.2 Setting cut-offs.html

9. Setting cut-offs.html

/9. PD model monitoring/

1. PD model monitoring via assessing population stability.mp4

1. PD model monitoring via assessing population stability.srt

2. PD model monitoring via assessing population stability.html

3. Population stability index preprocessing.mp4

3. Population stability index preprocessing.srt

4. Population stability index calculation and interpretation.mp4

4. Population stability index calculation and interpretation.srt

4.1 Monitoring with comments.html

4.2 Monitoring.html

5. Population stability index calculation and interpretation.html

6. Homework building an updated PD model.html

6.1 Dataset with new data (loan_data_2015.csv).html

/

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