minpy-ai (MinAI)
Einfache Machine-Learning-Library fuer Anfaenger. Keine Extra-Pakete noetig.
Install
pip install minpy-ai
Nutzung
import MinAI as ai
X, y = ai.MakeBlobs()
model, score, *_ = ai.QuickTrain("knn", X=X, y=y, k=3)
print(score)
print(ai.Predict(model, [2, 2]))
Features
- CSV laden, Train/Test-Split, Normalisieren
- Modelle: linear, knn, logistic, tree, neural net
- Score, Predict, Save/Load
Ausfuehrliche Anleitung: siehe Repository-Ordner Anleitungen/MinAI.md.
1 maintainer
Metadata
1 maintainer
Release files for minpy-ai 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 | |
|---|---|---|---|
| minpy_ai-0.1.0.tar.gz | 10.6 kB | Details |
Built distribution (wheel)
| File | Interpreter | ABI | Platform | Reset |
|---|---|---|---|---|
| minpy_ai-0.1.0-py3-none-any.whl | Python 3 | none | any | Details |
Total release size: 21.2 kB
Release files / minpy_ai-0.1.0.tar.gz
| Download URL | minpy_ai-0.1.0.tar.gz |
|---|---|
| Size | 10.6 kB |
| Tags | Source |
|
SHA-256 checksum How to use checksums |
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No |
| Uploaded via |
twine/7.0.0 CPython/3.12.7
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Release files / minpy_ai-0.1.0-py3-none-any.whl
| Download URL | minpy_ai-0.1.0-py3-none-any.whl |
|---|---|
| Size | 10.7 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/3.12.7
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