mllabcode
Source code for eight regression lab experiments (NumPy/SciPy/statsmodels basics, linear, multiple, polynomial and logistic regression, time series, imbalanced data).
Install
pip install mllabcode
Use
from mllabcode import code
print(code(1)) # source of experiment 1, as a string
code(n) accepts 1 to 8 and raises ValueError for anything else.
From a terminal: python -m mllabcode 1.
The package only returns the source text. To run an experiment you still need the libraries it imports (numpy, scipy, pandas, statsmodels, scikit-learn, matplotlib) and, for experiments 6 and 8, the dataset files they read.
Metadata
Release files for mllabcode 0.1.0
For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.
Source distribution (sdist)
| File | Size | Uploaded | |
|---|---|---|---|
| mllabcode-0.1.0.tar.gz | 9.4 kB | Details |
Built distribution (wheel)
| File | Interpreter | ABI | Platform | Reset |
|---|---|---|---|---|
| mllabcode-0.1.0-py3-none-any.whl | Python 3 | none | any | Details |
Total release size: 21.5 kB
Release files / mllabcode-0.1.0.tar.gz
| Download URL | mllabcode-0.1.0.tar.gz |
|---|---|
| Size | 9.4 kB |
| Tags | Source |
|
SHA-256 checksum How to use checksums |
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No |
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twine/7.0.0 CPython/3.13.14
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Release files / mllabcode-0.1.0-py3-none-any.whl
| Download URL | mllabcode-0.1.0-py3-none-any.whl |
|---|---|
| Size | 12.1 kB |
| Tags | Python 3 |
|
SHA-256 checksum How to use checksums |
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Uploaded using Trusted Publishing? What is trusted publishing? |
No |
| Uploaded via |
twine/7.0.0 CPython/3.13.14
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