dnn-time-series
Automated deep learning prediction modeling package for time-series data.
To test it out, go to Guide.ipynb and Run All.
1 maintainer
Metadata
1 maintainer
Release files for dnntime 0.3.2
For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.
Source distribution (sdist)
| File | Size | Uploaded | |
|---|---|---|---|
| dnntime-0.3.2.tar.gz | 2.6 MB | Details |
Built distribution (wheel)
| File | Interpreter | ABI | Platform | Reset |
|---|---|---|---|---|
| dnntime-0.3.2-py3-none-any.whl | Python 3 | none | any | Details |
Total release size: 2.6 MB
Release files / dnntime-0.3.2.tar.gz
| Download URL | dnntime-0.3.2.tar.gz |
|---|---|
| Size | 2.6 MB |
| 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/3.1.1 pkginfo/1.5.0.1 requests/2.22.0 setuptools/45.2.0 requests-toolbelt/0.9.1 tqdm/4.42.1 CPython/3.6.9
|
Release files / dnntime-0.3.2-py3-none-any.whl
| Download URL | dnntime-0.3.2-py3-none-any.whl |
|---|---|
| Size | 33.2 kB |
| Tags | Python 3 |
|
SHA-256 checksum How to use checksums |
8a8425474fa5ddf7d53a260e089a7321cddbc89035a2903ccd94e99baf39a58c
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BLAKE2b-256 checksum How to use checksums |
fb3aa2827fecd10d2cccf8f18d60a27a4f29136527bcf33c99be00d500e8f540
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| Upload date | |
|
Uploaded using Trusted Publishing? What is trusted publishing? |
No |
| Uploaded via |
twine/3.1.1 pkginfo/1.5.0.1 requests/2.22.0 setuptools/45.2.0 requests-toolbelt/0.9.1 tqdm/4.42.1 CPython/3.6.9
|
