NeurEco introduces a new generation of neural networks, based on parsimony. Using NeurEco’s parsimonious approach, the resources required for implementing artificial intelligence are reduced by several orders of magnitude. This includes reduction in the necessary amount of learning data, computing resources, development time, and energy consumption.
NeurEco is an ANN (artificial neural network) factory. It generates parsimonious ANN models automatically, using only the learning data provided by the user.
The real NeurEco ships as GPU-specific wheels from the Adagos package index. If
this module is importable, you installed the PyPI placeholder (i.e. pip install
neureco without the Adagos index), so importing it fails loudly with the
correct install instructions.
For a detailed description of the product, please read the documentation at: https://www.adagos.com/
Metadata
Release files for neureco 0.0.1
For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.
Source distribution (sdist)
| File | Size | Uploaded | Provenance | |
|---|---|---|---|---|
| neureco-0.0.1.tar.gz | 2.1 kB | Without provenance | Details |
Built distribution (wheel)
| File | Interpreter | ABI | Platform | Reset |
|---|---|---|---|---|
| neureco-0.0.1-py3-none-any.whl | Python 3 | none | any | Details |
Total release size: 4.4 kB
Release files / neureco-0.0.1.tar.gz
| Download URL | neureco-0.0.1.tar.gz |
|---|---|
| Size | 2.1 kB |
| Tags | Source |
|
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twine/7.0.0 CPython/3.14.3
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Release files / neureco-0.0.1-py3-none-any.whl
| Download URL | neureco-0.0.1-py3-none-any.whl |
|---|---|
| Size | 2.3 kB |
| Tags | Python 3 |
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SHA-256 checksum How to use checksums |
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No |
| Uploaded via |
twine/7.0.0 CPython/3.14.3
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Security for neureco 0.0.1
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