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| [CourseClub.Me].url |
48б |
| [CourseClub.Me].url |
48б |
| [CourseClub.Me].url |
48б |
| [CourseClub.Me].url |
48б |
| [CourseClub.Me].url |
48б |
| [DesireCourse.Net].url |
51б |
| [DesireCourse.Net].url |
51б |
| [DesireCourse.Net].url |
51б |
| [DesireCourse.Net].url |
51б |
| [DesireCourse.Net].url |
51б |
| 1.1 Calculating expected loss with comments.html |
207б |
| 1.1 Calculating probability of default for a single customer with comments.html |
187б |
| 1.1 EAD model estimation and interpretation with comments.html |
202б |
| 1.1 Importing the data into Python with comments.html |
188б |
| 1.1 LCDataDictionary.xlsx |
19.60Кб |
| 1.1 LGD and EAD models independent variables with comments.html |
202б |
| 1.1 LGD model preparing the inputs with comments.html |
202б |
| 1.1 Out-of-sample validation (test).html |
165б |
| 1.2 Calculating expected loss.html |
185б |
| 1.2 Calculating probability of default for a single customer.html |
165б |
| 1.2 Data preparation with comments.html |
188б |
| 1.2 EAD model estimation and interpretation.html |
180б |
| 1.2 Importing the data into Python.html |
166б |
| 1.2 LGD and EAD models independent variables..html |
180б |
| 1.2 loan_data_2007_2014_preprocessed.csv.html |
144б |
| 1.2 Out-of-sample validation (test) with comments.html |
187б |
| 1.3 Data Preparation.html |
166б |
| 1.3 LGD model preparing the inputs.html |
180б |
| 1.3 loan_data_2007_2014_preprocessed.csv.html |
144б |
| 1.4 Dataset for the course.html |
131б |
| 1. Calculating expected loss.mp4 |
126.70Мб |
| 1. Calculating expected loss.srt |
20.20Кб |
| 1. Calculating probability of default for a single customer.mp4 |
39.75Мб |
| 1. Calculating probability of default for a single customer.srt |
5.55Кб |
| 1. EAD model estimation and interpretation.mp4 |
48.01Мб |
| 1. EAD model estimation and interpretation.srt |
8.06Кб |
| 1. How is the PD model going to look like.mp4 |
37.59Мб |
| 1. How is the PD model going to look like.srt |
5.28Кб |
| 1. Importing the data into Python.mp4 |
32.86Мб |
| 1. Importing the data into Python.srt |
5.60Кб |
| 1. LGD and EAD models independent variables..mp4 |
50.03Мб |
| 1. LGD and EAD models independent variables..srt |
8.29Кб |
| 1. LGD model preparing the inputs.mp4 |
24.24Мб |
| 1. LGD model preparing the inputs.srt |
4.39Кб |
| 1. Our example consumer loans. A first look at the dataset.mp4 |
36.70Мб |
| 1. Our example consumer loans. A first look at the dataset.srt |
3.99Кб |
| 1. Out-of-sample validation (test).mp4 |
52.43Мб |
| 1. Out-of-sample validation (test).srt |
8.79Кб |
| 1. PD model monitoring via assessing population stability.mp4 |
39.03Мб |
| 1. PD model monitoring via assessing population stability.srt |
6.85Кб |
| 1. Setting up the environment - Do not skip, please!.mp4 |
5.99Мб |
| 1. Setting up the environment - Do not skip, please!.srt |
1.30Кб |
| 1. The PD model. Logistic regression with dummy variables.mp4 |
60.51Мб |
| 1. The PD model. Logistic regression with dummy variables.srt |
10.55Кб |
| 1. What does the course cover.mp4 |
72.92Мб |
| 1. What does the course cover.srt |
7.98Кб |
| 10.1 Check for missing values and clean the data Homework - Solution.html |
166б |
| 10.1 LGD model combining stage 1 and stage 2.html |
180б |
| 10.2 Check for missing values and clean the data Homework - Solution with comments.html |
188б |
| 10.2 LGD model combining stage 1 and stage 2 with comments.html |
202б |
| 10. Check for missing values and clean Homework.html |
668б |
| 10. Data preparation. Splitting data.html |
141б |
| 10. Different facility types (asset classes) and credit risk modeling approaches.mp4 |
104.45Мб |
| 10. Different facility types (asset classes) and credit risk modeling approaches.srt |
11.96Кб |
| 10. LGD model combining stage 1 and stage 2.mp4 |
23.97Мб |
| 10. LGD model combining stage 1 and stage 2.srt |
4.23Кб |
| 10. Setting cut-offs. Homework.html |
957б |
| 11.1 Data preparation. An example with comments.html |
188б |
| 11.1 PD model complete with comments.html |
177б |
| 11.2 Data preparation. An example.html |
166б |
| 11.2 PD model complete.html |
155б |
| 11. Data preparation. An example.mp4 |
49.90Мб |
| 11. Data preparation. An example.srt |
11.11Кб |
| 11. Different facility types (asset classes) and credit risk modeling approaches.html |
141б |
| 11. LGD model combining stage 1 and stage 2.html |
141б |
| 11. PD model logistic regression notebooks.html |
73б |
| 12.1 Dataset with new data (loan_data_2015.csv).html |
126б |
| 12. Data preparation. An example.html |
141б |
| 12. Homework building an updated LGD model.html |
1.43Кб |
| 13.1 Data preparation. Preprocessing discrete variables automating calculations.html |
166б |
| 13.2 Data preparation. Preprocessing discrete variables automating calculations with comments.html |
188б |
| 13. Data preparation. Preprocessing discrete variables automating calculations.mp4 |
43.72Мб |
| 13. Data preparation. Preprocessing discrete variables automating calculations.srt |
7.80Кб |
| 14. Data preparation. Preprocessing discrete variables automating calculations.html |
141б |
| 15.1 Data preparation. Preprocessing discrete variables visualizing results with comments.html |
188б |
| 15.2 Data preparation. Preprocessing discrete variables visualizing results.html |
166б |
| 15. Data preparation. Preprocessing discrete variables visualizing results.mp4 |
66.35Мб |
| 15. Data preparation. Preprocessing discrete variables visualizing results.srt |
12.91Кб |
| 16.1 Data preparation. Preprocessing discrete variables creating dummies (Part 1) with comments.html |
188б |
| 16.2 Data preparation. Preprocessing discrete variables creating dummies (Part 1).html |
166б |
| 16. Data preparation. Preprocessing discrete variables creating dummies (Part 1).mp4 |
49.71Мб |
| 16. Data preparation. Preprocessing discrete variables creating dummies (Part 1).srt |
9.52Кб |
| 17. Data preparation. Preprocessing discrete variables creating dummies (Part 1).html |
141б |
| 18.1 Data preparation. Preprocessing discrete variables creating dummies (Part 2).html |
167б |
| 18.2 Data preparation. Preprocessing discrete variables creating dummies (Part 2) with comments.html |
189б |
| 18. Data preparation. Preprocessing discrete variables creating dummies (Part 2).mp4 |
93.29Мб |
| 18. Data preparation. Preprocessing discrete variables creating dummies (Part 2).srt |
15.06Кб |
| 19. Data preparation. Preprocessing discrete variables creating dummies (Part 2).html |
141б |
| 2.1 Creating a scorecard with comments.html |
187б |
| 2.1 LGD model testing the model with comments.html |
202б |
| 2.2 Creating a scorecard.html |
165б |
| 2.2 LGD model testing the model.html |
180б |
| 2. Calculating expected loss.html |
141б |
| 2. Creating a scorecard.mp4 |
97.45Мб |
| 2. Creating a scorecard.srt |
16.75Кб |
| 2. EAD model estimation and interpretation.html |
141б |
| 2. How is the PD model going to look like.html |
141б |
| 2. Importing the data into Python.html |
141б |
| 2. LGD and EAD models independent variables.html |
141б |
| 2. LGD model testing the model.mp4 |
42.67Мб |
| 2. LGD model testing the model.srt |
6.84Кб |
| 2. Our example consumer loans. A first look at the dataset.html |
141б |
| 2. Out-of-sample validation (test).html |
141б |
| 2. PD model monitoring via assessing population stability.html |
141б |
| 2. The PD model. Logistic regression with dummy variables.html |
141б |
| 2. What is credit risk and why is it important.mp4 |
58.17Мб |
| 2. What is credit risk and why is it important.srt |
6.09Кб |
| 2. Why Python and why Jupyter.mp4 |
29.24Мб |
| 2. Why Python and why Jupyter.srt |
6.43Кб |
| 20.1 Data preparation. Preprocessing discrete variables. Homework with comments.html |
189б |
| 20.2 Data preparation. Preprocessing discrete variables Homework - Soluton.html |
167б |
| 20. Data preparation. Preprocessing discrete variables. Homework..html |
1.23Кб |
| 21.1 Data preparation. Preprocessing continuous variables Automating calculations with comments.html |
189б |
| 21.2 Data preparation. Preprocessing continuous variables Automating calculations.html |
167б |
| 21. Data preparation. Preprocessing continuous variables Automating calculations.mp4 |
45.06Мб |
| 21. Data preparation. Preprocessing continuous variables Automating calculations.srt |
6.63Кб |
| 22. Data preparation. Preprocessing continuous variables Automating calculations.html |
141б |
| 23.1 Data preparation. Preprocessing continuous variables creating dummies (Part 1).html |
167б |
| 23.2 Data preparation. Preprocessing continuous variables creating dummies (Part 1) with comments.html |
189б |
| 23. Data preparation. Preprocessing continuous variables creating dummies (Part 1).mp4 |
44.03Мб |
| 23. Data preparation. Preprocessing continuous variables creating dummies (Part 1).srt |
9.83Кб |
| 24. Data preparation. Preprocessing continuous variables creating dummies (Part 1).html |
141б |
| 25.1 Data preparation. Preprocessing continuous variables creating dummies (Part 2).html |
167б |
| 25.2 Data preparation. Preprocessing continuous variables creating dummies (Part 2) with comments.html |
189б |
| 25. Data preparation. Preprocessing continuous variables creating dummies (Part 2).mp4 |
111.79Мб |
| 25. Data preparation. Preprocessing continuous variables creating dummies (Part 2).srt |
19.37Кб |
| 26. Data preparation. Preprocessing continuous variables creating dummies (Part 2).html |
141б |
| 27.1 Data preparation. Preprocessing continuous variables creating dummies. Homework with comments.html |
189б |
| 27.2 Data preparation. Preprocessing continuous variables creating dummies. Homework.html |
167б |
| 27. Data preparation. Preprocessing continuous variables creating dummies. Homework.html |
1.90Кб |
| 28.1 Data preparation. Preprocessing continuous variables creating dummies (Part 3).html |
167б |
| 28.2 Data preparation. Preprocessing continuous variables creating dummies (Part 3) with comments.html |
189б |
| 28. Data preparation. Preprocessing continuous variables creating dummies (Part 3).mp4 |
100.95Мб |
| 28. Data preparation. Preprocessing continuous variables creating dummies (Part 3).srt |
16.86Кб |
| 29. Data preparation. Preprocessing continuous variables creating dummies (Part 3).html |
141б |
| 3.1 Calculating expected loss complete notebook with comments.html |
207б |
| 3.1 Dataset for the course.html |
131б |
| 3.1 Dependent variable GoodBad.html |
166б |
| 3.1 EAD model validation.html |
180б |
| 3.1 Evaluation of model performance accuracy and area under the curve (AUC) with comments.html |
187б |
| 3.1 LGD and EAD models dependent variables.html |
180б |
| 3.1 Loading the data and selecting the features.html |
165б |
| 3.1 Preprocessing few continuous variables with comments.html |
188б |
| 3.2 Calculating expected loss complete notebook.html |
185б |
| 3.2 Dependent variable GoodBad with comments.html |
188б |
| 3.2 EAD model validation with comments.html |
202б |
| 3.2 Evaluation of model performance accuracy and area under the curve (AUC).html |
165б |
| 3.2 LGD and EAD models dependent variables with comments.html |
202б |
| 3.2 Loading the data and selecting the features with comments.html |
187б |
| 3.2 Preprocessing few continuous variables.html |
166б |
| 3. Creating a scorecard.html |
141б |
| 3. Dependent variable Good Bad (default) definition.mp4 |
38.97Мб |
| 3. Dependent variable Good Bad (default) definition.srt |
7.13Кб |
| 3. Dependent variables and independent variables.mp4 |
65.88Мб |
| 3. Dependent variables and independent variables.srt |
8.02Кб |
| 3. EAD model validation.mp4 |
29.89Мб |
| 3. EAD model validation.srt |
5.65Кб |
| 3. Evaluation of model performance accuracy and area under the curve (AUC).mp4 |
75.90Мб |
| 3. Evaluation of model performance accuracy and area under the curve (AUC).srt |
14.40Кб |
| 3. Homework calculate expected loss on more recent data.html |
974б |
| 3. Installing Anaconda.mp4 |
29.26Мб |
| 3. Installing Anaconda.srt |
4.55Кб |
| 3. LGD and EAD models dependent variables.mp4 |
40.31Мб |
| 3. LGD and EAD models dependent variables.srt |
6.89Кб |
| 3. LGD model testing the model.html |
141б |
| 3. Loading the data and selecting the features.mp4 |
43.26Мб |
| 3. Loading the data and selecting the features.srt |
7.36Кб |
| 3. Population stability index preprocessing.mp4 |
105.25Мб |
| 3. Population stability index preprocessing.srt |
14.75Кб |
| 3. Preprocessing few continuous variables.mp4 |
83.70Мб |
| 3. Preprocessing few continuous variables.srt |
17.31Кб |
| 3. What is credit risk and why is it important.html |
141б |
| 30.1 Data preparation. Preprocessing continuous variables creating dummies Homework - Solution.html |
167б |
| 30.2 Data preparation. Preprocessing continuous variables creating dummies. Homework with comments.html |
189б |
| 30. Data preparation. Preprocessing continuous variables creating dummies. Homework.html |
1.38Кб |
| 31.1 Data preparation. Preprocessing the test dataset with comments.html |
189б |
| 31.2 Data preparation. Preprocessing the test dataset.html |
167б |
| 31. Data preparation. Preprocessing the test dataset.mp4 |
29.95Мб |
| 31. Data preparation. Preprocessing the test dataset.srt |
5.51Кб |
| 32.1 PD model data preparation.html |
156б |
| 32.2 PD model data preparation with comments.html |
178б |
| 32. PD model data preparation notebooks.html |
85б |
| 4.1 Calculating credit score.html |
165б |
| 4.1 LGD model estimating the accuracy of the model with comments.html |
202б |
| 4.1 Monitoring.html |
155б |
| 4.1 PD model estimation.html |
165б |
| 4.2 Calculating credit score with comments.html |
187б |
| 4.2 LGD model estimating the accuracy of the model.html |
180б |
| 4.2 Monitoring with comments.html |
177б |
| 4.2 PD model estimation with comments.html |
187б |
| 4. Calculating credit score.mp4 |
41.14Мб |
| 4. Calculating credit score.srt |
7.54Кб |
| 4. Completing 100%.html |
1.88Кб |
| 4. Dependent variable Good Bad (default) definition.html |
141б |
| 4. Dependent variables and independent variables.html |
141б |
| 4. EAD model validation.html |
141б |
| 4. Evaluation of model performance accuracy and area under the curve (AUC).html |
141б |
| 4. Expected loss (EL) and its components PD, LGD and EAD.mp4 |
47.95Мб |
| 4. Expected loss (EL) and its components PD, LGD and EAD.srt |
5.24Кб |
| 4. Jupyter Dashboard - Part 1.mp4 |
11.57Мб |
| 4. Jupyter Dashboard - Part 1.srt |
3.22Кб |
| 4. LGD and EAD models dependent variables.html |
141б |
| 4. LGD model estimating the accuracy of the model.mp4 |
34.84Мб |
| 4. LGD model estimating the accuracy of the model.srt |
5.95Кб |
| 4. PD model estimation.mp4 |
24.92Мб |
| 4. PD model estimation.srt |
4.93Кб |
| 4. Population stability index calculation and interpretation.mp4 |
91.64Мб |
| 4. Population stability index calculation and interpretation.srt |
14.26Кб |
| 4. Preprocessing few continuous variables.html |
141б |
| 5.1 Build a logistic regression model with p-values.html |
165б |
| 5.1 Evaluation of model performance Gini and Kolmogorov-Smirnov with comments.html |
187б |
| 5.1 LGD and EAD models distribution of recovery rates and credit conversion factors with comments.html |
202б |
| 5.1 LGD model saving the model with comments.html |
202б |
| 5.1 Preprocessing few continuous variables Homework - Solution.html |
166б |
| 5.1 Shortcuts-for-Jupyter.pdf |
629.17Кб |
| 5.2 Build a logistic regression model with p-values with comments.html |
187б |
| 5.2 Evaluation of model performance Gini and Kolmogorov-Smirnov.html |
165б |
| 5.2 LGD and EAD models distribution of recovery rates and credit conversion factors.html |
180б |
| 5.2 LGD model saving the model.html |
180б |
| 5.2 Preprocessing few continuous variables Homework - Solution with comments.html |
188б |
| 5. Build a logistic regression model with p-values.mp4 |
102.45Мб |
| 5. Build a logistic regression model with p-values.srt |
14.49Кб |
| 5. Calculating credit score.html |
141б |
| 5. Evaluation of model performance Gini and Kolmogorov-Smirnov.mp4 |
69.86Мб |
| 5. Evaluation of model performance Gini and Kolmogorov-Smirnov.srt |
13.46Кб |
| 5. Expected loss (EL) and its components PD, LGD and EAD.html |
141б |
| 5. Fine classing, weight of evidence, and coarse classing.mp4 |
55.34Мб |
| 5. Fine classing, weight of evidence, and coarse classing.srt |
8.67Кб |
| 5. Homework building an updated EAD model.html |
875б |
| 5. Jupyter Dashboard - Part 2.mp4 |
23.92Мб |
| 5. Jupyter Dashboard - Part 2.srt |
6.64Кб |
| 5. LGD and EAD models distribution of recovery rates and credit conversion factors.mp4 |
40.04Мб |
| 5. LGD and EAD models distribution of recovery rates and credit conversion factors.srt |
7.71Кб |
| 5. LGD model saving the model.mp4 |
23.83Мб |
| 5. LGD model saving the model.srt |
4.02Кб |
| 5. Population stability index calculation and interpretation.html |
141б |
| 5. Preprocessing few continuous variables Homework.html |
919б |
| 6.1 Dataset with new data (loan_data_2015.csv).html |
126б |
| 6.1 From credit score to PD.html |
165б |
| 6.1 LGD model stage 2 – linear regression.html |
180б |
| 6.1 Preprocessing few discrete variables with comments.html |
188б |
| 6.2 From credit score to PD with comments.html |
187б |
| 6.2 LGD model stage 2 – linear regression with comments.html |
202б |
| 6.2 Preprocessing few discrete variables.html |
166б |
| 6. Build a logistic regression model with p-values.html |
141б |
| 6. Capital adequacy, regulations, and the Basel II accord.mp4 |
51.03Мб |
| 6. Capital adequacy, regulations, and the Basel II accord.srt |
5.79Кб |
| 6. Evaluation of model performance Gini and Kolmogorov-Smirnov.html |
141б |
| 6. Fine classing, weight of evidence, and coarse classing.html |
141б |
| 6. From credit score to PD.mp4 |
23.20Мб |
| 6. From credit score to PD.srt |
4.14Кб |
| 6. Homework building an updated PD model.html |
820б |
| 6. Installing the sklearn package.mp4 |
9.65Мб |
| 6. Installing the sklearn package.srt |
1.92Кб |
| 6. LGD and EAD models distribution of recovery rates and credit conversion factors.html |
141б |
| 6. LGD model stage 2 – linear regression.mp4 |
36.06Мб |
| 6. LGD model stage 2 – linear regression.srt |
5.26Кб |
| 6. Preprocessing few discrete variables.mp4 |
46.30Мб |
| 6. Preprocessing few discrete variables.srt |
8.93Кб |
| 7. Capital adequacy, regulations, and the Basel II accord.html |
141б |
| 7. From credit score to PD.html |
141б |
| 7. Information value.mp4 |
44.70Мб |
| 7. Information value.srt |
6.85Кб |
| 7. Interpreting the coefficients in the PD model.mp4 |
35.23Мб |
| 7. Interpreting the coefficients in the PD model.srt |
7.99Кб |
| 7. LGD model stage 2 – linear regression with comments.html |
141б |
| 7. Preprocessing few discrete variables.html |
141б |
| 8.1 Check for missing values and clean.html |
166б |
| 8.1 LGD model stage 2 – linear regression evaluation.html |
180б |
| 8.1 Setting cut-offs.html |
165б |
| 8.2 Check for missing values and clean with comments.html |
188б |
| 8.2 LGD model stage 2 – linear regression evaluation with comments.html |
202б |
| 8.2 Setting cut-offs with comments.html |
187б |
| 8. Basel II approaches SA, F-IRB, and A-IRB.mp4 |
102.44Мб |
| 8. Basel II approaches SA, F-IRB, and A-IRB.srt |
12.63Кб |
| 8. Check for missing values and clean.mp4 |
25.08Мб |
| 8. Check for missing values and clean.srt |
4.55Кб |
| 8. Information value.html |
141б |
| 8. Interpreting the coefficients in the PD model.html |
141б |
| 8. LGD model stage 2 – linear regression evaluation.mp4 |
26.80Мб |
| 8. LGD model stage 2 – linear regression evaluation.srt |
4.56Кб |
| 8. Setting cut-offs.mp4 |
76.02Мб |
| 8. Setting cut-offs.srt |
11.41Кб |
| 9.1 Data preparation. Splitting data.html |
166б |
| 9.2 Data preparation. Splitting data with comments.html |
188б |
| 9. Basel II approaches SA, F-IRB, and A-IRB.html |
141б |
| 9. Check for missing values and clean.html |
141б |
| 9. Data preparation. Splitting data.mp4 |
59.38Мб |
| 9. Data preparation. Splitting data.srt |
11.54Кб |
| 9. LGD model stage 2 – linear regression evaluation.html |
141б |
| 9. Setting cut-offs.html |
141б |