https://github.com/chibuikeeugene/loan-amount-prediction
A machine learning program that estimates the amount of loan to be issued as seen in the dataset given. This program uses a simple hist gradient boosting regressor algorithm to estimate the likely loan user should be eligible for.
https://github.com/chibuikeeugene/loan-amount-prediction
docker docker-compose evidentlyai fastapi hyperopt mlflow prefect-orchestration
Last synced: about 1 year ago
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A machine learning program that estimates the amount of loan to be issued as seen in the dataset given. This program uses a simple hist gradient boosting regressor algorithm to estimate the likely loan user should be eligible for.
- Host: GitHub
- URL: https://github.com/chibuikeeugene/loan-amount-prediction
- Owner: chibuikeeugene
- Created: 2024-02-23T01:04:30.000Z (over 2 years ago)
- Default Branch: main
- Last Pushed: 2024-08-15T11:26:49.000Z (almost 2 years ago)
- Last Synced: 2025-04-05T05:46:20.509Z (over 1 year ago)
- Topics: docker, docker-compose, evidentlyai, fastapi, hyperopt, mlflow, prefect-orchestration
- Language: Jupyter Notebook
- Homepage:
- Size: 13 MB
- Stars: 1
- Watchers: 1
- Forks: 2
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
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README
# LOAN AMOUNT PREDICTION
A machine learning program that estimates the amount of loan to be issued as seen in the dataset given. This program uses a **simple hist gradient boosting regressor algorithm** to estimate the likely loan user should be eligible for.
## Data set and its description
| Data | Description |
|-------------------|----------------------------------------|
| Loan_ID | Unique loan request identifier |
| Gender | sex of the user |
| Married | Marital status |
| Dependents | Number of dependents |
| Education | if the candidate is graduate or not |
| Self_Employed | if the user is working for himself |
| ApplicantIncome | total income of the candidate |
| CoapplicantIncome | total income of the borrower's partner |
| LoanAmount | Amount requested |
| Loan_Amount_Term | in months |
| Credit_History | 1(okay or eligible), 0(Not eligible) |
| Property_Area | nature of where the borrower live |
| Loan_Status | if loan was granted or not |
## Dependencies and packages
1. python = "^3.9"
2. numpy = "^1.26.4"
3. pandas = "^2.2.2"
4. pydantic = "^2.7.3"
5. scikit-learn = "^1.5.0"
6. strictyaml = "^1.7.3"
7. feature-engine = "^1.8.0"
8. joblib = "^1.4.2"
9. mlflow = "^2.13.2"
10. ipykernel = "^6.29.4"
11. hyperopt = "^0.2.7"
12. scipy = "^1.13.1"
13. loguru = "^0.7.2"
## Source code link
Source code link:
[Github link](https://github.com/chibuikeeugene/loan-amount-prediction.git)
## Snapshots
![API Documentation 1]()
![API Documentation 2]()
![API Documentation 3]()
![AWS Deploy Documentation 4]()
![AWS Deploy Documentation 5]()