Ecosyste.ms: Awesome
An open API service indexing awesome lists of open source software.
https://github.com/gititsid/visaverdict
A ML project to predict possibility of US Visa approval
https://github.com/gititsid/visaverdict
classification python3 random-forest-classifier scikit-learn
Last synced: 26 days ago
JSON representation
A ML project to predict possibility of US Visa approval
- Host: GitHub
- URL: https://github.com/gititsid/visaverdict
- Owner: gititsid
- License: other
- Created: 2024-08-30T10:18:49.000Z (2 months ago)
- Default Branch: main
- Last Pushed: 2024-09-12T13:57:10.000Z (about 2 months ago)
- Last Synced: 2024-10-12T23:43:18.209Z (26 days ago)
- Topics: classification, python3, random-forest-classifier, scikit-learn
- Language: Jupyter Notebook
- Homepage:
- Size: 1.33 MB
- Stars: 0
- Watchers: 1
- Forks: 0
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
- License: LICENSE
Awesome Lists containing this project
README
# VisaVerdict
A Machine Learning project to predict the likelihood of US Visa approval
----
## Workflow:
1. Update config: `config/config.yaml`
2. Update the entity: `src/VisVerdict/entity/config_entity.py`
3. Update the configuration manager: `src/VisVerdict/config/configuration.py`
4. Update the components: `src/VisVerdict/components`
5. Update the pipeline: `src/VisVerdict/pipeline`
6. Update entry point: `main.py`
7. Update application: `app.py`
---
## Project Organization:
```
|── .dvc <- dvc cache, config, remote info
|── .github <- ci/cd workflows
|── artifacts <- o/p of pipe that are needed for execution of next pipeline
|── config <- configurations for all the components of the project
|── docs <- documentation of the project src code
|── flowcharts <- flowcharts of the project components, overall, etc.
|── logs <- log file generated while running the component/s
|── mlruns <- MLFlow: all ml experiments and their artifacts
|── notebooks <- jupyter-notebooks
| |__ data <- sample data to do experiments in the notebook
|
|── references <- quick reference for the project. e.g. research papers
|── reports <- reports generated in the project life-cycle
| |__ figures
|
|── scripts <- shell scripts to invoke operations from the command line
| |── setup.sh <- initial setup of the project
| |__ test.sh <- run tests
|
|── src
| |__ ProjectName
| |── __init__.py
| |── logger.py <- A custom logger to stream logs in a terminal/log in file
| |── exception.py <- A custom exception handler for the project
| |── components <- components of the ml pipeline
| | |── __init__.py
| | |── data_ingestion.py
| | |── data_valaidation.py
| | |── data_preprocessing.py
| | |── data_transformation.py
| | |── model_training.py
| | |── model_evaluation.py
| | |__ prediction.py
| |
| |── config <- configuration for the component
| | |── configration.py
| | |__ __init__.py
| |
| |── constants <- constants used in the project
| | |── __init__.py
| | |── PROJECT_ROOT
| |
| |── entity < datasclass for each component
| | |── __init__.py
| | |__ config_entity.py
| |
| |── pipeline <- all steps in the pipeline
| | |── __init__.py
| | |── data_ingestion.py
| | |── data_valaidation.py
| | |── data_preprocessing.py
| | |── data_transformation.py
| | |── model_training.py
| | |── model_evaluation.py
| | |__ predict.py
| |
| |── utils <- all utilities used in the project
| |── __init__.py
| |__ common.py <- common utilities for the project
|
|── static <- assets/CSS/JS
| |── assets
| |__ img
|
|── templates <- HTML
| |── index.html
| |__ results.html
|
|── tests <- tests for the project
| |── unit
| |__ integration
|
|── .dvcignore
|── .gitignore
|── app.py <- expose application via API
|── DockerFile <- containerize the application
|── dvc.yaml <- DVC pipeline
|── LICENSE
|── main.py <- entry point for the project
|── README.md
|── requirements.txt
|── setup.py <- package project
|__ template.py <- creates empty files/folders
```
---
Project Owner: [Siddharth Kumar](https://www.linktr.ee/linkitsid)
---