Numenta Platform for Intelligent Computing: a machine intelligence platform that implements the HTM learning algorithms. HTM is a detailed computational theory of the neocortex. At the core of HTM are time-based continuous learning algorithms that store and recall spatial and temporal patterns. NuPIC is suited to a variety of problems, particularly anomaly detection and prediction of streaming data sources.
For more information, see http://numenta.org or the NuPIC wiki at https://github.com/numenta/nupic/wiki.
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Release files for anomalyHTM 1.0.0
For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.
Source distribution (sdist)
| File | Size | Uploaded | |
|---|---|---|---|
| anomalyHTM-1.0.0.tar.gz | 537.5 kB | Details |
Built distribution (wheel)
| File | Interpreter | ABI | Platform | Reset |
|---|---|---|---|---|
| anomalyHTM-1.0.0-py2-none-any.whl | Python 2 | none | any | Details |
Total release size: 1.2 MB
Release files / anomalyHTM-1.0.0.tar.gz
| Download URL | anomalyHTM-1.0.0.tar.gz |
|---|---|
| Size | 537.5 kB |
| Tags | Source |
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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/1.15.0 pkginfo/1.7.0 requests/2.25.1 setuptools/44.1.1 requests-toolbelt/0.9.1 tqdm/4.61.0 CPython/2.7.18
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Release files / anomalyHTM-1.0.0-py2-none-any.whl
| Download URL | anomalyHTM-1.0.0-py2-none-any.whl |
|---|---|
| Size | 688.5 kB |
| Tags | Python 2 |
|
SHA-256 checksum How to use checksums |
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BLAKE2b-256 checksum How to use checksums |
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Uploaded using Trusted Publishing? What is trusted publishing? |
No |
| Uploaded via |
twine/1.15.0 pkginfo/1.7.0 requests/2.25.1 setuptools/44.1.1 requests-toolbelt/0.9.1 tqdm/4.61.0 CPython/2.7.18
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