ML Workflow Automation Tool
The main goal is to simplify the machine learning workflow for users with different levels of expertise, through a CLI app. We ask the user for certain inputs like the dataset file or folder, and the type of ML problem and target variable (if necessary). We then perform standard data preprocessing (not dataset specific) and feature selection (if necessary), and train relevant models for the data and present a comparative analysis of the models trained, along with downloadable model weight files in the joblib format.
Key Features
- Compare various machine learning algorithms
- Performance comparison
- Model training result comparison through CLI
- All model files stored as a zip of joblib files
Preview
Deployment
Find out which ML model suits your needs by installing our package from pypi
pip install curdrice
Usage
Use the following command for help -
curdrice --help
Template code
curdrice -p <db_path> -d <zip_name> <type> <target>
Acknowledgements
Authors
Release files for curdrice-v2 0.1
For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.
Source distribution (sdist)
| File | Size | Uploaded | |
|---|---|---|---|
| curdrice_v2-0.1.tar.gz | 8.7 kB | Details |
Built distribution (wheel)
| File | Interpreter | ABI | Platform | Reset |
|---|---|---|---|---|
| curdrice_v2-0.1-py3-none-any.whl | Python 3 | none | any | Details |
Total release size: 17.7 kB
Release files / curdrice_v2-0.1.tar.gz
| Download URL | curdrice_v2-0.1.tar.gz |
|---|---|
| Size | 8.7 kB |
| Tags | Source |
|
SHA-256 checksum How to use checksums |
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BLAKE2b-256 checksum How to use checksums |
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| Upload date | |
|
Uploaded using Trusted Publishing? What is trusted publishing? |
No |
| Uploaded via |
twine/5.1.1 CPython/3.12.4
|
Release files / curdrice_v2-0.1-py3-none-any.whl
| Download URL | curdrice_v2-0.1-py3-none-any.whl |
|---|---|
| Size | 9.1 kB |
| Tags | Python 3 |
|
SHA-256 checksum How to use checksums |
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BLAKE2b-256 checksum How to use checksums |
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|
| Upload date | |
|
Uploaded using Trusted Publishing? What is trusted publishing? |
No |
| Uploaded via |
twine/5.1.1 CPython/3.12.4
|