Download Udemy - Credit Risk Modeling in Python 2020 [Desire Course] Torrent

Torrent Contents Size: 3.2 GB

Udemy - Credit Risk Modeling in Python 2020 [Desire Course]

▼ show more 286 files

1. Calculating expected loss.mp4	MP4	126.7 MB
1. Calculating expected loss.srt	SRT	20.2 KB
1. Calculating probability of default for a single customer.mp4	MP4	39.7 MB
1. Calculating probability of default for a single customer.srt	SRT	5.5 KB
1. EAD model estimation and interpretation.mp4	MP4	48 MB
1. EAD model estimation and interpretation.srt	SRT	8.1 KB
1. How is the PD model going to look like.mp4	MP4	37.6 MB
1. How is the PD model going to look like.srt	SRT	5.3 KB
1. Importing the data into Python.mp4	MP4	32.9 MB
1. Importing the data into Python.srt	SRT	5.6 KB
1. LGD and EAD models independent variables..mp4	MP4	50 MB
1. LGD and EAD models independent variables..srt	SRT	8.3 KB
1. LGD model preparing the inputs.mp4	MP4	24.2 MB
1. LGD model preparing the inputs.srt	SRT	4.4 KB
1. Our example consumer loans. A first look at the dataset.mp4	MP4	36.7 MB
1. Our example consumer loans. A first look at the dataset.srt	SRT	4 KB
1. Out-of-sample validation (test).mp4	MP4	52.4 MB
1. Out-of-sample validation (test).srt	SRT	8.8 KB
1. PD model monitoring via assessing population stability.mp4	MP4	39 MB
1. PD model monitoring via assessing population stability.srt	SRT	6.9 KB
1. Setting up the environment - Do not skip, please!.mp4	MP4	6 MB
1. Setting up the environment - Do not skip, please!.srt	SRT	1.3 KB
1. The PD model. Logistic regression with dummy variables.mp4	MP4	60.5 MB
1. The PD model. Logistic regression with dummy variables.srt	SRT	10.6 KB
1. What does the course cover.mp4	MP4	72.9 MB
1. What does the course cover.srt	SRT	8 KB
1.1 Calculating expected loss with comments.html	HTML	204 B
1.1 Calculating probability of default for a single customer with comments.html	HTML	204 B
1.1 EAD model estimation and interpretation with comments.html	HTML	204 B
1.1 Importing the data into Python with comments.html	HTML	204 B
1.1 LCDataDictionary.xlsx	XLSX	19.6 KB
1.1 LGD and EAD models independent variables with comments.html	HTML	204 B
1.1 LGD model preparing the inputs with comments.html	HTML	204 B
1.1 Out-of-sample validation (test).html	HTML	204 B
1.2 Calculating expected loss.html	HTML	204 B
1.2 Calculating probability of default for a single customer.html	HTML	204 B
1.2 Data preparation with comments.html	HTML	204 B
1.2 EAD model estimation and interpretation.html	HTML	204 B
1.2 Importing the data into Python.html	HTML	204 B
1.2 LGD and EAD models independent variables..html	HTML	204 B
1.2 Out-of-sample validation (test) with comments.html	HTML	204 B
1.2 loan_data_2007_2014_preprocessed.csv.html	HTML	102 B
1.3 Data Preparation.html	HTML	204 B
1.3 LGD model preparing the inputs.html	HTML	204 B
1.3 loan_data_2007_2014_preprocessed.csv.html	HTML	102 B
1.4 Dataset for the course.html	HTML	102 B
10. Check for missing values and clean Homework.html	HTML	716 B
10. Data preparation. Splitting data.html	HTML	102 B
10. Different facility types (asset classes) and credit risk modeling approaches.mp4	MP4	104.4 MB
10. Different facility types (asset classes) and credit risk modeling approaches.srt	SRT	12 KB
10. LGD model combining stage 1 and stage 2.mp4	MP4	24 MB
10. LGD model combining stage 1 and stage 2.srt	SRT	4.2 KB
10. Setting cut-offs. Homework.html	HTML	921 B
10.1 Check for missing values and clean the data Homework - Solution.html	HTML	204 B
10.1 LGD model combining stage 1 and stage 2.html	HTML	204 B
10.2 Check for missing values and clean the data Homework - Solution with comments.html	HTML	204 B
10.2 LGD model combining stage 1 and stage 2 with comments.html	HTML	204 B
11. Data preparation. An example.mp4	MP4	49.9 MB
11. Data preparation. An example.srt	SRT	11.1 KB
11. Different facility types (asset classes) and credit risk modeling approaches.html	HTML	102 B
11. LGD model combining stage 1 and stage 2.html	HTML	102 B
11. PD model logistic regression notebooks.html	HTML	102 B
11.1 Data preparation. An example with comments.html	HTML	204 B
11.1 PD model complete with comments.html	HTML	204 B
11.2 Data preparation. An example.html	HTML	204 B
11.2 PD model complete.html	HTML	204 B
12. Data preparation. An example.html	HTML	102 B
12. Homework building an updated LGD model.html	HTML	1.4 KB
12.1 Dataset with new data (loan_data_2015.csv).html	HTML	102 B
13. Data preparation. Preprocessing discrete variables automating calculations.mp4	MP4	43.7 MB
13. Data preparation. Preprocessing discrete variables automating calculations.srt	SRT	7.8 KB
13.1 Data preparation. Preprocessing discrete variables automating calculations.html	HTML	204 B
13.2 Data preparation. Preprocessing discrete variables automating calculations with comments.html	HTML	204 B
14. Data preparation. Preprocessing discrete variables automating calculations.html	HTML	102 B
15. Data preparation. Preprocessing discrete variables visualizing results.mp4	MP4	66.3 MB
15. Data preparation. Preprocessing discrete variables visualizing results.srt	SRT	12.9 KB
15.1 Data preparation. Preprocessing discrete variables visualizing results with comments.html	HTML	204 B
15.2 Data preparation. Preprocessing discrete variables visualizing results.html	HTML	204 B
16. Data preparation. Preprocessing discrete variables creating dummies (Part 1).mp4	MP4	49.7 MB
16. Data preparation. Preprocessing discrete variables creating dummies (Part 1).srt	SRT	9.5 KB
16.1 Data preparation. Preprocessing discrete variables creating dummies (Part 1) with comments.html	HTML	204 B
16.2 Data preparation. Preprocessing discrete variables creating dummies (Part 1).html	HTML	204 B
17. Data preparation. Preprocessing discrete variables creating dummies (Part 1).html	HTML	102 B
18. Data preparation. Preprocessing discrete variables creating dummies (Part 2).mp4	MP4	93.3 MB
18. Data preparation. Preprocessing discrete variables creating dummies (Part 2).srt	SRT	15.1 KB
18.1 Data preparation. Preprocessing discrete variables creating dummies (Part 2).html	HTML	204 B
18.2 Data preparation. Preprocessing discrete variables creating dummies (Part 2) with comments.html	HTML	204 B
19. Data preparation. Preprocessing discrete variables creating dummies (Part 2).html	HTML	102 B
2. Calculating expected loss.html	HTML	102 B
2. Creating a scorecard.mp4	MP4	97.4 MB
2. Creating a scorecard.srt	SRT	16.8 KB
2. EAD model estimation and interpretation.html	HTML	102 B
2. How is the PD model going to look like.html	HTML	102 B
2. Importing the data into Python.html	HTML	102 B
2. LGD and EAD models independent variables.html	HTML	102 B
2. LGD model testing the model.mp4	MP4	42.7 MB
2. LGD model testing the model.srt	SRT	6.8 KB
2. Our example consumer loans. A first look at the dataset.html	HTML	102 B
2. Out-of-sample validation (test).html	HTML	102 B
2. PD model monitoring via assessing population stability.html	HTML	102 B
2. The PD model. Logistic regression with dummy variables.html	HTML	102 B
2. What is credit risk and why is it important.mp4	MP4	58.2 MB
2. What is credit risk and why is it important.srt	SRT	6.1 KB
2. Why Python and why Jupyter.mp4	MP4	29.2 MB
2. Why Python and why Jupyter.srt	SRT	6.4 KB
2.1 Creating a scorecard with comments.html	HTML	204 B
2.1 LGD model testing the model with comments.html	HTML	204 B
2.2 Creating a scorecard.html	HTML	204 B
2.2 LGD model testing the model.html	HTML	204 B
20. Data preparation. Preprocessing discrete variables. Homework..html	HTML	1.2 KB
20.1 Data preparation. Preprocessing discrete variables. Homework with comments.html	HTML	204 B
20.2 Data preparation. Preprocessing discrete variables Homework - Soluton.html	HTML	204 B
21. Data preparation. Preprocessing continuous variables Automating calculations.mp4	MP4	45.1 MB
21. Data preparation. Preprocessing continuous variables Automating calculations.srt	SRT	6.6 KB
21.1 Data preparation. Preprocessing continuous variables Automating calculations with comments.html	HTML	204 B
21.2 Data preparation. Preprocessing continuous variables Automating calculations.html	HTML	204 B
22. Data preparation. Preprocessing continuous variables Automating calculations.html	HTML	102 B
23. Data preparation. Preprocessing continuous variables creating dummies (Part 1).mp4	MP4	44 MB
23. Data preparation. Preprocessing continuous variables creating dummies (Part 1).srt	SRT	9.8 KB
23.1 Data preparation. Preprocessing continuous variables creating dummies (Part 1).html	HTML	204 B
23.2 Data preparation. Preprocessing continuous variables creating dummies (Part 1) with comments.html	HTML	204 B
24. Data preparation. Preprocessing continuous variables creating dummies (Part 1).html	HTML	102 B
25. Data preparation. Preprocessing continuous variables creating dummies (Part 2).mp4	MP4	111.8 MB
25. Data preparation. Preprocessing continuous variables creating dummies (Part 2).srt	SRT	19.4 KB
25.1 Data preparation. Preprocessing continuous variables creating dummies (Part 2).html	HTML	204 B
25.2 Data preparation. Preprocessing continuous variables creating dummies (Part 2) with comments.html	HTML	204 B
26. Data preparation. Preprocessing continuous variables creating dummies (Part 2).html	HTML	102 B
27. Data preparation. Preprocessing continuous variables creating dummies. Homework.html	HTML	1.9 KB
27.1 Data preparation. Preprocessing continuous variables creating dummies. Homework with comments.html	HTML	204 B
27.2 Data preparation. Preprocessing continuous variables creating dummies. Homework.html	HTML	204 B
28. Data preparation. Preprocessing continuous variables creating dummies (Part 3).mp4	MP4	101 MB
28. Data preparation. Preprocessing continuous variables creating dummies (Part 3).srt	SRT	16.9 KB
28.1 Data preparation. Preprocessing continuous variables creating dummies (Part 3).html	HTML	204 B
28.2 Data preparation. Preprocessing continuous variables creating dummies (Part 3) with comments.html	HTML	204 B
29. Data preparation. Preprocessing continuous variables creating dummies (Part 3).html	HTML	102 B
3. Creating a scorecard.html	HTML	102 B
3. Dependent variable Good Bad (default) definition.mp4	MP4	39 MB
3. Dependent variable Good Bad (default) definition.srt	SRT	7.1 KB
3. Dependent variables and independent variables.mp4	MP4	65.9 MB
3. Dependent variables and independent variables.srt	SRT	8 KB
3. EAD model validation.mp4	MP4	29.9 MB
3. EAD model validation.srt	SRT	5.6 KB
3. Evaluation of model performance accuracy and area under the curve (AUC).mp4	MP4	75.9 MB
3. Evaluation of model performance accuracy and area under the curve (AUC).srt	SRT	14.4 KB
3. Homework calculate expected loss on more recent data.html	HTML	1 KB
3. Installing Anaconda.mp4	MP4	29.3 MB
3. Installing Anaconda.srt	SRT	4.5 KB
3. LGD and EAD models dependent variables.mp4	MP4	40.3 MB
3. LGD and EAD models dependent variables.srt	SRT	6.9 KB
3. LGD model testing the model.html	HTML	102 B
3. Loading the data and selecting the features.mp4	MP4	43.3 MB
3. Loading the data and selecting the features.srt	SRT	7.4 KB
3. Population stability index preprocessing.mp4	MP4	105.2 MB
3. Population stability index preprocessing.srt	SRT	14.8 KB
3. Preprocessing few continuous variables.mp4	MP4	83.7 MB
3. Preprocessing few continuous variables.srt	SRT	17.3 KB
3. What is credit risk and why is it important.html	HTML	102 B
3.1 Calculating expected loss complete notebook with comments.html	HTML	204 B
3.1 Dataset for the course.html	HTML	102 B
3.1 Dependent variable GoodBad.html	HTML	204 B
3.1 EAD model validation.html	HTML	204 B
3.1 Evaluation of model performance accuracy and area under the curve (AUC) with comments.html	HTML	204 B
3.1 LGD and EAD models dependent variables.html	HTML	204 B
3.1 Loading the data and selecting the features.html	HTML	204 B
3.1 Preprocessing few continuous variables with comments.html	HTML	204 B
3.2 Calculating expected loss complete notebook.html	HTML	204 B
3.2 Dependent variable GoodBad with comments.html	HTML	204 B
3.2 EAD model validation with comments.html	HTML	204 B
3.2 Evaluation of model performance accuracy and area under the curve (AUC).html	HTML	204 B
3.2 LGD and EAD models dependent variables with comments.html	HTML	204 B
3.2 Loading the data and selecting the features with comments.html	HTML	204 B
3.2 Preprocessing few continuous variables.html	HTML	204 B
30. Data preparation. Preprocessing continuous variables creating dummies. Homework.html	HTML	1.4 KB
30.1 Data preparation. Preprocessing continuous variables creating dummies Homework - Solution.html	HTML	204 B
30.2 Data preparation. Preprocessing continuous variables creating dummies. Homework with comments.html	HTML	204 B
31. Data preparation. Preprocessing the test dataset.mp4	MP4	30 MB
31. Data preparation. Preprocessing the test dataset.srt	SRT	5.5 KB
31.1 Data preparation. Preprocessing the test dataset with comments.html	HTML	204 B
31.2 Data preparation. Preprocessing the test dataset.html	HTML	204 B
32. PD model data preparation notebooks.html	HTML	102 B
32.1 PD model data preparation.html	HTML	204 B
32.2 PD model data preparation with comments.html	HTML	204 B
4. Calculating credit score.mp4	MP4	41.1 MB
4. Calculating credit score.srt	SRT	7.5 KB
4. Completing 100%.html	HTML	1.9 KB
4. Dependent variable Good Bad (default) definition.html	HTML	102 B
4. Dependent variables and independent variables.html	HTML	102 B
4. EAD model validation.html	HTML	102 B
4. Evaluation of model performance accuracy and area under the curve (AUC).html	HTML	102 B
4. Expected loss (EL) and its components PD, LGD and EAD.mp4	MP4	47.9 MB
4. Expected loss (EL) and its components PD, LGD and EAD.srt	SRT	5.2 KB
4. Jupyter Dashboard - Part 1.mp4	MP4	11.6 MB
4. Jupyter Dashboard - Part 1.srt	SRT	3.2 KB
4. LGD and EAD models dependent variables.html	HTML	102 B
4. LGD model estimating the accuracy of the model.mp4	MP4	34.8 MB
4. LGD model estimating the accuracy of the model.srt	SRT	5.9 KB
4. PD model estimation.mp4	MP4	24.9 MB
4. PD model estimation.srt	SRT	4.9 KB
4. Population stability index calculation and interpretation.mp4	MP4	91.6 MB
4. Population stability index calculation and interpretation.srt	SRT	14.3 KB
4. Preprocessing few continuous variables.html	HTML	102 B
4.1 Calculating credit score.html	HTML	204 B
4.1 LGD model estimating the accuracy of the model with comments.html	HTML	204 B
4.1 Monitoring.html	HTML	204 B
4.1 PD model estimation.html	HTML	204 B
4.2 Calculating credit score with comments.html	HTML	204 B
4.2 LGD model estimating the accuracy of the model.html	HTML	204 B
4.2 Monitoring with comments.html	HTML	204 B
4.2 PD model estimation with comments.html	HTML	204 B
5. Build a logistic regression model with p-values.mp4	MP4	102.5 MB
5. Build a logistic regression model with p-values.srt	SRT	14.5 KB
5. Calculating credit score.html	HTML	102 B
5. Evaluation of model performance Gini and Kolmogorov-Smirnov.mp4	MP4	69.9 MB
5. Evaluation of model performance Gini and Kolmogorov-Smirnov.srt	SRT	13.5 KB
5. Expected loss (EL) and its components PD, LGD and EAD.html	HTML	102 B
5. Fine classing, weight of evidence, and coarse classing.mp4	MP4	55.3 MB
5. Fine classing, weight of evidence, and coarse classing.srt	SRT	8.7 KB
5. Homework building an updated EAD model.html	HTML	921 B
5. Jupyter Dashboard - Part 2.mp4	MP4	23.9 MB
5. Jupyter Dashboard - Part 2.srt	SRT	6.6 KB
5. LGD and EAD models distribution of recovery rates and credit conversion factors.mp4	MP4	40 MB
5. LGD and EAD models distribution of recovery rates and credit conversion factors.srt	SRT	7.7 KB
5. LGD model saving the model.mp4	MP4	23.8 MB
5. LGD model saving the model.srt	SRT	4 KB
5. Population stability index calculation and interpretation.html	HTML	102 B
5. Preprocessing few continuous variables Homework.html	HTML	921 B
5.1 Build a logistic regression model with p-values.html	HTML	204 B
5.1 Evaluation of model performance Gini and Kolmogorov-Smirnov with comments.html	HTML	204 B
5.1 LGD and EAD models distribution of recovery rates and credit conversion factors with comments.html	HTML	204 B
5.1 LGD model saving the model with comments.html	HTML	204 B
5.1 Preprocessing few continuous variables Homework - Solution.html	HTML	204 B
5.1 Shortcuts-for-Jupyter.pdf	PDF	629.2 KB
5.2 Build a logistic regression model with p-values with comments.html	HTML	204 B
5.2 Evaluation of model performance Gini and Kolmogorov-Smirnov.html	HTML	204 B
5.2 LGD and EAD models distribution of recovery rates and credit conversion factors.html	HTML	204 B
5.2 LGD model saving the model.html	HTML	204 B
5.2 Preprocessing few continuous variables Homework - Solution with comments.html	HTML	204 B
6. Build a logistic regression model with p-values.html	HTML	102 B
6. Capital adequacy, regulations, and the Basel II accord.mp4	MP4	51 MB
6. Capital adequacy, regulations, and the Basel II accord.srt	SRT	5.8 KB
6. Evaluation of model performance Gini and Kolmogorov-Smirnov.html	HTML	102 B
6. Fine classing, weight of evidence, and coarse classing.html	HTML	102 B
6. From credit score to PD.mp4	MP4	23.2 MB
6. From credit score to PD.srt	SRT	4.1 KB
6. Homework building an updated PD model.html	HTML	819 B
6. Installing the sklearn package.mp4	MP4	9.7 MB
6. Installing the sklearn package.srt	SRT	1.9 KB
6. LGD and EAD models distribution of recovery rates and credit conversion factors.html	HTML	102 B
6. LGD model stage 2 – linear regression.mp4	MP4	36.1 MB
6. LGD model stage 2 – linear regression.srt	SRT	5.3 KB
6. Preprocessing few discrete variables.mp4	MP4	46.3 MB
6. Preprocessing few discrete variables.srt	SRT	8.9 KB
6.1 Dataset with new data (loan_data_2015.csv).html	HTML	102 B
6.1 From credit score to PD.html	HTML	204 B
6.1 LGD model stage 2 – linear regression.html	HTML	204 B
6.1 Preprocessing few discrete variables with comments.html	HTML	204 B
6.2 From credit score to PD with comments.html	HTML	204 B
6.2 LGD model stage 2 – linear regression with comments.html	HTML	204 B
6.2 Preprocessing few discrete variables.html	HTML	204 B
7. Capital adequacy, regulations, and the Basel II accord.html	HTML	102 B
7. From credit score to PD.html	HTML	102 B
7. Information value.mp4	MP4	44.7 MB
7. Information value.srt	SRT	6.9 KB
7. Interpreting the coefficients in the PD model.mp4	MP4	35.2 MB
7. Interpreting the coefficients in the PD model.srt	SRT	8 KB
7. LGD model stage 2 – linear regression with comments.html	HTML	102 B
7. Preprocessing few discrete variables.html	HTML	102 B
8. Basel II approaches SA, F-IRB, and A-IRB.mp4	MP4	102.4 MB
8. Basel II approaches SA, F-IRB, and A-IRB.srt	SRT	12.6 KB
8. Check for missing values and clean.mp4	MP4	25.1 MB
8. Check for missing values and clean.srt	SRT	4.6 KB
8. Information value.html	HTML	102 B
8. Interpreting the coefficients in the PD model.html	HTML	102 B
8. LGD model stage 2 – linear regression evaluation.mp4	MP4	26.8 MB
8. LGD model stage 2 – linear regression evaluation.srt	SRT	4.6 KB
8. Setting cut-offs.mp4	MP4	76 MB
8. Setting cut-offs.srt	SRT	11.4 KB
8.1 Check for missing values and clean.html	HTML	204 B
8.1 LGD model stage 2 – linear regression evaluation.html	HTML	204 B
8.1 Setting cut-offs.html	HTML	204 B
8.2 Check for missing values and clean with comments.html	HTML	204 B
8.2 LGD model stage 2 – linear regression evaluation with comments.html	HTML	204 B
8.2 Setting cut-offs with comments.html	HTML	204 B
9. Basel II approaches SA, F-IRB, and A-IRB.html	HTML	102 B
9. Check for missing values and clean.html	HTML	102 B
9. Data preparation. Splitting data.mp4	MP4	59.4 MB
9. Data preparation. Splitting data.srt	SRT	11.5 KB
9. LGD model stage 2 – linear regression evaluation.html	HTML	102 B
9. Setting cut-offs.html	HTML	102 B
9.1 Data preparation. Splitting data.html	HTML	204 B
9.2 Data preparation. Splitting data with comments.html	HTML	204 B
[CourseClub.Me].url	URL	0 B
[DesireCourse.Net].url	URL	0 B

Description

Show full description

Related Torrents

TORRENT NAME	SIZE	FILES	AGE	SEED	LEECH	SOURCE
Udemy - Wallet Campus - Intro To Credit Posted by freecoursewb in Other Posted in Other 0 3.1 GB 8 months ago freecoursewb	Size 3.1 GB	Files 47	Age 8 months ago	Seeds 0	Leechs 0	Source
Udemy - Introduction To Private Credit Fund Posted by freecoursewb in Other Posted in Other 0 816.9 MB 10 months ago freecoursewb	Size 816.9 MB	Files 11	Age 10 months ago	Seeds 0	Leechs 0	Source
Udemy - Credit Scoring with Machine Learning - A Practical Guide Posted by freecoursewb in Other Posted in Other 0 926.5 MB 10 months ago freecoursewb	Size 926.5 MB	Files 61	Age 10 months ago	Seeds 0	Leechs 0	Source
Udemy - Credit Risk Essentials - Analytics, Ai and Underwriting Posted by freecoursewb in Other Posted in Other 0 2 GB 11 months ago freecoursewb	Size 2 GB	Files 31	Age 11 months ago	Seeds 0	Leechs 0	Source
Udemy - Learn Banking Credit Analysis Through Case Studies Posted by freecoursewb in Other Posted in Other 6 1.6 GB 1 year ago freecoursewb	Size 1.6 GB	Files 62	Age 1 year ago	Seeds 6	Leechs 5	Source

Udemy - Credit Risk Modeling in Python 2020 [Desire Course]

Torrent Contents Size: 3.2 GB

Description

Related Torrents

Location

Trackers

Latest News

Latest Searches

Sites In Our Index

Popular Tags

Tracker name
udp://tracker.coppersurfer.tk:6969/announce
udp://tracker.leechers-paradise.org:6969/announce
udp://9.rarbg.to:2710/announce
udp://exodus.desync.com:6969/announce
udp://tracker.uw0.xyz:6969/announce
udp://open.stealth.si:80/announce
udp://tracker.tiny-vps.com:6969/announce
udp://open.demonii.si:1337/announc4
udp://public-tracker.zooki.xyz:6969/announce
udp://forever.publictracker.xyz:6969/announce
udp://tracker.cyberia.is:6969/announce
udp://api.bitumconference.ru:6969/announce
udp://discord.heihachi.pw:6969/announce
udp://fe.dealclub.de:6969/announce
udp://tracker.zer0day.to:1337/announce
udp://tracker.leechers-paradise.org:6969/announce
udp://coppersurfer.tk:6969/announce