What is this package and what does it do?
This package is meant to ease the lives of the analysts and data scientists by providing generalised functions for preprocessing of dataframes and images which are commonly used in Machine Learning. Additionally, using this package, one can also call various machine learning models as base models with customised data, target, and parameters to check how different models are performing.
Please check the docs: ricebowl documentation
How to use this package?
Simply do:
pip install ricebowl
and import and use after having a look at the documentation
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Release files for ricebowl 0.5.2
For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.
Source distribution (sdist)
| File | Size | Uploaded | |
|---|---|---|---|
| ricebowl-0.5.2.tar.gz | 9.6 kB | Details |
Built distribution (wheel)
| File | Interpreter | ABI | Platform | Reset |
|---|---|---|---|---|
| ricebowl-0.5.2-py3-none-any.whl | Python 3 | none | any | Details |
Total release size: 21.8 kB
Release files / ricebowl-0.5.2.tar.gz
| Download URL | ricebowl-0.5.2.tar.gz |
|---|---|
| Size | 9.6 kB |
| Tags | Source |
|
SHA-256 checksum How to use checksums |
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twine/3.2.0 pkginfo/1.5.0.1 requests/2.24.0 setuptools/49.3.1 requests-toolbelt/0.9.1 tqdm/4.48.2 CPython/3.6.9
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Release files / ricebowl-0.5.2-py3-none-any.whl
| Download URL | ricebowl-0.5.2-py3-none-any.whl |
|---|---|
| Size | 12.2 kB |
| Tags | Python 3 |
|
SHA-256 checksum How to use checksums |
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Uploaded using Trusted Publishing? What is trusted publishing? |
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| Uploaded via |
twine/3.2.0 pkginfo/1.5.0.1 requests/2.24.0 setuptools/49.3.1 requests-toolbelt/0.9.1 tqdm/4.48.2 CPython/3.6.9
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