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365 Data Science - Credit Risk Modeling in Python [CoursesGhar]

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文件列表

  1. 1. Introduction/1. What is credit risk and why is it important.mp4 55MB
  2. 9. PD model monitoring/2. Population stability index - preprocessing.mp4 53MB
  3. 1. Introduction/2. Expected loss (EL) and its components - PD, LGD and EAD.mp4 46MB
  4. 13. Calculating expected loss/1. Calculating expected loss.mp4 46MB
  5. 6. PD model estimation/4. Build a logistic regression model with p-values..mp4 42MB
  6. 8. Applying the PD model for decision making/2. Creating a scorecard.mp4 40MB
  7. 5. PD model_ data preparation/13. Data preparation. Preprocessing continuous variables - creating dummies (Part 2).mp4 38MB
  8. 5. PD model_ data preparation/14. Data preparation. Preprocessing continuous variables - creating dummies (Part 3).mp4 36MB
  9. 5. PD model_ data preparation/10. Data preparation. Preprocessing discrete variables - creating dummies (Part 2).mp4 35MB
  10. 9. PD model monitoring/3. Population stability index - calculation and interpretation.mp4 33MB
  11. 1. Introduction/5. Different facility types (asset classes) and credit risk modeling approaches.mp4 32MB
  12. 1. Introduction/4. Basel II approaches - SA, F-IRB, and A-IRB.mp4 30MB
  13. 8. Applying the PD model for decision making/5. Setting cut-offs.mp4 30MB
  14. 4. General preprocessing/2. Preprocessing few continuous variables.mp4 30MB
  15. 7. PD model validation (test)/2. Evaluation of model performance - accuracy and area under the curve (AUC).mp4 25MB
  16. 7. PD model validation (test)/3. Evaluation of model performance - Gini and Kolmogorov-Smirnov..mp4 23MB
  17. 5. PD model_ data preparation/8. Data preparation. Preprocessing discrete variables - visualizing results.mp4 23MB
  18. 6. PD model estimation/1. The PD model. Logistic regression with dummy variables.mp4 20MB
  19. 5. PD model_ data preparation/5. Data preparation. Splitting data.mp4 20MB
  20. 7. PD model validation (test)/1. Out-of-sample validation (test)..mp4 20MB
  21. 5. PD model_ data preparation/11. Data preparation. Preprocessing continuous variables - automating calculations.mp4 19MB
  22. 3. Dataset description/2. Dependent variables and independent variables.mp4 19MB
  23. 4. General preprocessing/3. Preprocessing few discrete variables.mp4 19MB
  24. 10. LGD and EAD models/1. LGD and EAD models - independent variables.mp4 18MB
  25. 5. PD model_ data preparation/9. Data Preparation. Preprocessing Discrete Variables - Creating Dummies (Part 1).mp4 18MB
  26. 12. EAD model/1. EAD model estimation and interpretation.mp4 18MB
  27. 5. PD model_ data preparation/6. Data preparation. An example.mp4 18MB
  28. 11. LGD model/2. LGD model - testing the model.mp4 17MB
  29. 5. PD model_ data preparation/7. Data preparation. Preprocessing discrete variables - automating calculations.mp4 16MB
  30. 4. General preprocessing/1. Importing the data into Python.mp4 16MB
  31. 5. PD model_ data preparation/3. Fine classing, weight of evidence, and coarse classing.mp4 16MB
  32. 6. PD model estimation/2. Loading the data and selecting the features.mp4 16MB
  33. 1. Introduction/3. Capital adequacy, regulations, and the Basel II accord.mp4 15MB
  34. 8. Applying the PD model for decision making/3. Calculating credit score.mp4 15MB
  35. 11. LGD model/5. LGD model - stage 2 – linear regression.mp4 15MB
  36. 5. PD model_ data preparation/12. Data preparation. Preprocessing continuous variables - creating dummies (Part 1).mp4 14MB
  37. 3. Dataset description/1. Our example - consumer loans. A first look at the dataset.mp4 14MB
  38. 10. LGD and EAD models/3. LGD and EAD models - distribution of recovery rates and credit conversion factors.mp4 14MB
  39. 10. LGD and EAD models/2. LGD and EAD models - dependent variables.mp4 14MB
  40. 8. Applying the PD model for decision making/1. Calculating probability of default for a single customer.mp4 13MB
  41. 5. PD model_ data preparation/4. Information value.mp4 13MB
  42. 11. LGD model/3. LGD model - estimating the accuracy of the model.mp4 12MB
  43. 5. PD model_ data preparation/2. Dependent variable - Good_ Bad (default) definition.mp4 12MB
  44. 5. PD model_ data preparation/1. How is the PD model going to look like.mp4 12MB
  45. 5. PD model_ data preparation/15. Data preparation. Preprocessing the test dataset.mp4 12MB
  46. 6. PD model estimation/5. Interpreting the coefficients in the PD model.mp4 11MB
  47. 9. PD model monitoring/1. PD model monitoring via assessing population stability.mp4 11MB
  48. 12. EAD model/2. EAD model validation.mp4 10MB
  49. 11. LGD model/6. LGD model - stage 2 – linear regression evaluation.mp4 10MB
  50. 4. General preprocessing/4. Check for missing values and clean.mp4 9MB
  51. 2. Setting up the working environment/2. Why Python and why Jupyter.mp4 9MB
  52. 11. LGD model/7. LGD model - combining stage 1 and stage 2.mp4 9MB
  53. 6. PD model estimation/3. PD model estimation.mp4 9MB
  54. 2. Setting up the working environment/5. Jupyter Dashboard - Part 2.mp4 9MB
  55. 11. LGD model/1. LGD model - preparing the inputs.mp4 9MB
  56. 11. LGD model/4. LGD model - saving the model.mp4 8MB
  57. 2. Setting up the working environment/3. Installing Anaconda.mp4 8MB
  58. 8. Applying the PD model for decision making/4. From credit score to PD.mp4 7MB
  59. 2. Setting up the working environment/4. Jupyter Dashboard - Part 1.mp4 4MB
  60. 2. Setting up the working environment/6. Installing the sklearn package.mp4 3MB
  61. 2. Setting up the working environment/1. Setting up the environment - Do not skip, please!.mp4 2MB
  62. Uploaded by [Coursesghar.com].txt 1KB
  63. !! IMPORTANT Note !!.txt 298B
  64. !!! Please Support !!! [CoursesGhar.Com].txt 197B
  65. Join Our Telegram Group For More Updates !!!.url 138B
  66. 00. Websites You May Like/A1movies.com.pk.url 116B
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  68. Visit coursesghar.com for more awesome tutorials.url 114B