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GetFreeCourses.Co-Udemy-Credit Risk Modeling in Python 2020
magnet:?xt=urn:btih:0e53c1e731b21f58bfbc77652d1902f085e6dfb4&dn=GetFreeCourses.Co-Udemy-Credit Risk Modeling in Python 2020
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0e53c1e731b21f58bfbc77652d1902f085e6dfb4
infohash:
62
文件数量
3.16 GB
文件大小
2021-3-4 16:26
创建日期
2024-7-1 03:44
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相关分词
GetFreeCourses
Co-Udemy-Credit
Risk
Modeling
in
Python
2020
1. Introduction/1. What does the course cover.mp4 72.92 MB
1. Introduction/10. Different facility types (asset classes) and credit risk modeling approaches.mp4 104.45 MB
1. Introduction/2. What is credit risk and why is it important.mp4 58.17 MB
1. Introduction/4. Expected loss (EL) and its components PD, LGD and EAD.mp4 47.95 MB
1. Introduction/6. Capital adequacy, regulations, and the Basel II accord.mp4 51.03 MB
1. Introduction/8. Basel II approaches SA, F-IRB, and A-IRB.mp4 102.44 MB
10. LGD and EAD Models Preparing the data/1. LGD and EAD models independent variables..mp4 50.03 MB
10. LGD and EAD Models Preparing the data/3. LGD and EAD models dependent variables.mp4 40.31 MB
10. LGD and EAD Models Preparing the data/5. LGD and EAD models distribution of recovery rates and credit conversion factors.mp4 40.04 MB
11. LGD model/1. LGD model preparing the inputs.mp4 24.24 MB
11. LGD model/10. LGD model combining stage 1 and stage 2.mp4 23.97 MB
11. LGD model/2. LGD model testing the model.mp4 42.67 MB
11. LGD model/4. LGD model estimating the accuracy of the model.mp4 34.84 MB
11. LGD model/5. LGD model saving the model.mp4 23.83 MB
11. LGD model/6. LGD model stage 2 – linear regression.mp4 36.06 MB
11. LGD model/8. LGD model stage 2 – linear regression evaluation.mp4 26.8 MB
12. EAD model/1. EAD model estimation and interpretation.mp4 48.01 MB
12. EAD model/3. EAD model validation.mp4 29.89 MB
13. Calculating expected loss/1. Calculating expected loss.mp4 126.7 MB
2. Setting up the working environment/1. Setting up the environment - Do not skip, please!.mp4 5.99 MB
2. Setting up the working environment/2. Why Python and why Jupyter.mp4 29.24 MB
2. Setting up the working environment/3. Installing Anaconda.mp4 29.26 MB
2. Setting up the working environment/4. Jupyter Dashboard - Part 1.mp4 11.57 MB
2. Setting up the working environment/5. Jupyter Dashboard - Part 2.mp4 23.92 MB
2. Setting up the working environment/6. Installing the sklearn package.mp4 9.65 MB
3. Dataset description/1. Our example consumer loans. A first look at the dataset.mp4 36.7 MB
3. Dataset description/3. Dependent variables and independent variables.mp4 65.88 MB
4. General preprocessing/1. Importing the data into Python.mp4 32.86 MB
4. General preprocessing/3. Preprocessing few continuous variables.mp4 83.7 MB
4. General preprocessing/6. Preprocessing few discrete variables.mp4 46.3 MB
4. General preprocessing/8. Check for missing values and clean.mp4 25.08 MB
5. PD Model Data Preparation/1. How is the PD model going to look like.mp4 37.59 MB
5. PD Model Data Preparation/11. Data preparation. An example.mp4 49.9 MB
5. PD Model Data Preparation/13. Data preparation. Preprocessing discrete variables automating calculations.mp4 43.72 MB
5. PD Model Data Preparation/15. Data preparation. Preprocessing discrete variables visualizing results.mp4 66.35 MB
5. PD Model Data Preparation/16. Data preparation. Preprocessing discrete variables creating dummies (Part 1).mp4 49.71 MB
5. PD Model Data Preparation/18. Data preparation. Preprocessing discrete variables creating dummies (Part 2).mp4 93.29 MB
5. PD Model Data Preparation/21. Data preparation. Preprocessing continuous variables Automating calculations.mp4 45.06 MB
5. PD Model Data Preparation/23. Data preparation. Preprocessing continuous variables creating dummies (Part 1).mp4 44.03 MB
5. PD Model Data Preparation/25. Data preparation. Preprocessing continuous variables creating dummies (Part 2).mp4 111.79 MB
5. PD Model Data Preparation/28. Data preparation. Preprocessing continuous variables creating dummies (Part 3).mp4 100.95 MB
5. PD Model Data Preparation/3. Dependent variable Good Bad (default) definition.mp4 38.97 MB
5. PD Model Data Preparation/31. Data preparation. Preprocessing the test dataset.mp4 29.95 MB
5. PD Model Data Preparation/5. Fine classing, weight of evidence, and coarse classing.mp4 55.34 MB
5. PD Model Data Preparation/7. Information value.mp4 44.7 MB
5. PD Model Data Preparation/9. Data preparation. Splitting data.mp4 59.38 MB
6. PD model estimation/1. The PD model. Logistic regression with dummy variables.mp4 60.51 MB
6. PD model estimation/3. Loading the data and selecting the features.mp4 43.26 MB
6. PD model estimation/4. PD model estimation.mp4 24.92 MB
6. PD model estimation/5. Build a logistic regression model with p-values.mp4 102.45 MB
6. PD model estimation/7. Interpreting the coefficients in the PD model.mp4 35.23 MB
7. PD model validation/1. Out-of-sample validation (test).mp4 52.43 MB
7. PD model validation/3. Evaluation of model performance accuracy and area under the curve (AUC).mp4 75.9 MB
7. PD model validation/5. Evaluation of model performance Gini and Kolmogorov-Smirnov.mp4 69.86 MB
8. Applying the PD Model for decision making/1. Calculating probability of default for a single customer.mp4 39.75 MB
8. Applying the PD Model for decision making/2. Creating a scorecard.mp4 97.45 MB
8. Applying the PD Model for decision making/4. Calculating credit score.mp4 41.14 MB
8. Applying the PD Model for decision making/6. From credit score to PD.mp4 23.2 MB
8. Applying the PD Model for decision making/8. Setting cut-offs.mp4 76.02 MB
9. PD model monitoring/1. PD model monitoring via assessing population stability.mp4 39.03 MB
9. PD model monitoring/3. Population stability index preprocessing.mp4 105.25 MB
9. PD model monitoring/4. Population stability index calculation and interpretation.mp4 91.64 MB
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