:Search:

Udemy Credit Scoring with Machine Learning A Practical Guide

Torrent:
Magnet Download .torrent File
Info Hash: 9AF4D2F5B31E430726AA38D60523C4BD15E48720
Similar Posts:
Name Uploaded Size Se Le Upl. by
Udemy Credit Risk Modeling in Python 2020 Udemy Credit Risk Modeling in Python 2020
2023-10-28 3.2 GB 45 20 Fcw007
Udemy Credit Ratings in Financial Setup of Rating Agencies Udemy Credit Ratings in Financial Setup of Rating Agencies
2023-10-24 1.7 GB 0 0 freecoursewb
Udemy Credit Risk Analysis and Modeling 2022 Udemy Credit Risk Analysis and Modeling 2022
2023-10-24 1.0 GB 4 3 freecoursewb
Udemy Credit Rating Of Real Estate Developers Udemy Credit Rating Of Real Estate Developers
2023-10-23 553.1 MB 0 3 freecoursewb
Udemy Credit Policy Products Delivery Appraisal Risk and Rating Udemy Credit Policy Products Delivery Appraisal Risk and Rating
2023-10-23 1.7 GB 0 21 freecoursewb
Udemy Credit Rating By Rating Agencies Part 1 Udemy Credit Rating By Rating Agencies Part 1
2023-10-23 447.5 MB 0 0 freecoursewb
Udemy Credit Repair For Beginners Basics Of Credit Repair Udemy Credit Repair For Beginners Basics Of Credit Repair
2023-10-22 345.9 MB 5 1 freecoursewb
Udemy - Credit Risk Modeling in Python 2020 [Desire Course] Udemy - Credit Risk Modeling in Python 2020 [Desire Course]
2023-06-02 3.2 GB 17 7 CourseClub
Udemy Credit Risk Essentials Analytics Ai and Underwriting Udemy Credit Risk Essentials Analytics Ai and Underwriting
2025-06-21 2.0 GB 2 1 freecoursewb
Udemy Credit Scoring with Machine Learning A Practical Guide Udemy Credit Scoring with Machine Learning A Practical Guide
2025-07-31 926.5 MB 1 5 freecoursewb
Uploader: freecoursewb
Source: 1 Logo 1337x
Downloads: 6
Type: Tutorials
Language: English
Category: Other
Size: 926.5 MB
Added: July 31, 2025, 4:54 a.m.
Peers: Seeders: 1, Leechers: 5 (Last updated: 8 months, 2 weeks ago)
Tracker Data:
Tracker Seeders Leechers Completed
udp://open.stealth.si:80/announce 0 1 0
udp://exodus.desync.com:6969/announce (Failed to scrape UDP tracker) 0 0 0
udp://tracker.cyberia.is:6969/announce (Failed to scrape UDP tracker) 0 0 0
udp://tracker.opentrackr.org:1337/announce 1 1 6
udp://tracker.torrent.eu.org:451/announce 0 1 0
udp://explodie.org:6969/announce 0 1 0
udp://tracker.birkenwald.de:6969/announce 0 1 0
udp://tracker.moeking.me:6969/announce (Failed to scrape UDP tracker) 0 0 0
udp://ipv4.tracker.harry.lu:80/announce (Failed to scrape UDP tracker) 0 0 0
udp://tracker.therarbg.to:6969/announce 0 0 0
Files:
  1. Get Bonus Downloads Here.url 180 bytes
  2. 1 -Course Introduction.mp4 13.5 MB
  3. 1 -Introduction.mp4 7.4 MB
  4. 2 -Loan Application Process.mp4 5.4 MB
  5. 3 -Credit Score.mp4 10.3 MB
  6. 4 -Credit Scoring.mp4 4.6 MB
  7. 5 -Risk-Based Pricing.mp4 8.5 MB
  8. 1 -Introduction.mp4 767.7 KB
  9. 2 -Installing Jupyter Notebook Using Anaconda.mp4 6.5 MB
  10. 2 -httpswww.url 56 bytes
  11. 3 -Jupyter Notebook Interface.mp4 35.7 MB
  12. 4 -Key Python Libraries for Data Analysis.mp4 25.6 MB
  13. 4 -check_libraries.ipynb 57.2 KB
  14. 4 -matplotlib.url 74 bytes
  15. 4 -pandas.url 48 bytes
  16. 4 -seaborn.url 49 bytes
  17. 5 -Dataset Analysis.mp4 22.0 MB
  18. 5 -credit_scoring_dataset.csv 1.7 MB
  19. 5 -demo_eda.ipynb 334.5 KB
  20. 1 -Introduction.mp4 714.6 KB
  21. 10 -Logistic Regression Classifier.mp4 24.2 MB
  22. 11 -Balancing False Positives and False Negatives.mp4 7.7 MB
  23. 12 -Logistic Regression Classifier – demo.mp4 78.6 MB
  24. 12 -credit_scoring_dataset.csv 1.7 MB
  25. 12 -logistic_regression.ipynb 87.6 KB
  26. 13 -DecisionTreeClassifier.url 113 bytes
  27. 13 -Random Forest.mp4 50.5 MB
  28. 13 -RandomForestClassifier.url 117 bytes
  29. 13 -decision_tree_visualization.ipynb 687.9 KB
  30. 14 -Decision Tree Structure.mp4 12.1 MB
  31. 14 -decision_tree_visualization.ipynb 687.9 KB
  32. 15 -Random Forest – demo.mp4 62.4 MB
  33. 15 -random_forest.ipynb 129.2 KB
  34. 16 -Scikit-learn Pipeline.mp4 6.5 MB
  35. 17 -Scikit-learn Pipeline – demo.mp4 89.7 MB
  36. 17 -random_forest_pipeline.ipynb 118.8 KB
  37. 18 -Saving and Loading Machine Learning Models for Predictions.mp4 12.3 MB
  38. 19 -Predictions with Random Forest Pipeline – demo.mp4 10.9 MB
  39. 19 -random_forest_pipeline_predictions.ipynb 8.7 KB
  40. 2 -Exploring the Credit Scoring Dataset.mp4 9.0 MB
  41. 2 -essential_features_for_effective_credit_scoring.ipynb 20.0 KB
  42. 20 -k-fold cross-validation.mp4 28.8 MB
  43. 21 -k-fold cross-validation – demo.mp4 70.7 MB
  44. 21 -random_forest_kfold.ipynb 8.7 KB
  45. 22 -ROC, AUC, and Cost-Based Metrics.mp4 33.4 MB
  46. 22 -auc_and_roc_curve.ipynb 65.0 KB
  47. 23 -Divergence Analysis.mp4 24.5 MB
  48. 23 -divergence_analysis.ipynb 158.8 KB
  49. 24 -Risk-Based Grouping.mp4 92.4 MB
  50. 24 -data.joblib 969.0 KB
  51. 24 -rf_model.joblib 27.5 MB
  52. 24 -risk_based_grouping.ipynb 168.2 KB
  53. 25 -Wrapping Up Key Takeaways and Next Steps.mp4 14.6 MB
  54. 3 -Types of Machine Learning.mp4 18.0 MB
  55. 4 -Machine Learning Workflow Overview.mp4 20.3 MB
  56. 5 -Introduction to Scikit-Learn.mp4 39.6 MB
  57. 6 -Confusion Matrix.mp4 9.1 MB
  58. 7 -Implications of False Positives in Credit Scoring.mp4 10.6 MB
  59. 8 -Implications of False Negatives in Credit Scoring.mp4 9.7 MB
  60. 9 -Performance Metrics.mp4 15.7 MB
  61. Bonus Resources.txt 70 bytes

Discussion