Quasi-randomized (neural) networks for regression, classification and time series forecasting
Metadata
Release files for nnetsauce 0.56.0
For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.
Source distribution (sdist)
| File | Size | Uploaded | |
|---|---|---|---|
| nnetsauce-0.56.0.tar.gz | 190.9 kB | Details |
Built distribution (wheel)
| File | Interpreter | ABI | Platform | Reset |
|---|---|---|---|---|
| nnetsauce-0.56.0-py3-none-any.whl | Python 3 | none | any | Details |
Total release size: 447.2 kB
Release files / nnetsauce-0.56.0.tar.gz
| Download URL | nnetsauce-0.56.0.tar.gz |
|---|---|
| Size | 190.9 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 | |
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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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Release files / nnetsauce-0.56.0-py3-none-any.whl
| Download URL | nnetsauce-0.56.0-py3-none-any.whl |
|---|---|
| Size | 256.3 kB |
| Tags | Python 3 |
|
SHA-256 checksum How to use checksums |
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BLAKE2b-256 checksum How to use checksums |
18e7ec7d04c8d5a51fced00fb2c895ed10b38c3a2b5b6f0a0969d10ea1dff1dc
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| Upload date | |
|
Uploaded using Trusted Publishing? What is trusted publishing? |
No |
| Uploaded via |
twine/7.0.0 CPython/3.13.14
|