DeepBay
This project was created with the objective of compile Machine Learning Architectures created using Tensorflow or Keras. The architectures must be provided as a ready-to-use Plug-and-Play module that can be easily integrated into any existing project or architecture design
Installation
You can use pip for install this from PyPi, just use:
pip install deepbay
1 maintainer
Release files for deepbay 0.8.3
For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.
Source distribution (sdist)
| File | Size | Uploaded | |
|---|---|---|---|
| deepbay-0.8.3.tar.gz | 4.4 kB | Details |
Built distribution (wheel)
| File | Interpreter | ABI | Platform | Reset |
|---|---|---|---|---|
| deepbay-0.8.3-py3-none-any.whl | Python 3 | none | any | Details |
Total release size: 11.9 kB
Release files / deepbay-0.8.3.tar.gz
| Download URL | deepbay-0.8.3.tar.gz |
|---|---|
| Size | 4.4 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/3.1.0 pkginfo/1.5.0.1 requests/2.22.0 setuptools/41.2.0 requests-toolbelt/0.9.1 tqdm/4.39.0 CPython/3.8.0
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Release files / deepbay-0.8.3-py3-none-any.whl
| Download URL | deepbay-0.8.3-py3-none-any.whl |
|---|---|
| Size | 7.5 kB |
| Tags | Python 3 |
|
SHA-256 checksum How to use checksums |
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BLAKE2b-256 checksum How to use checksums |
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| Upload date | |
|
Uploaded using Trusted Publishing? What is trusted publishing? |
No |
| Uploaded via |
twine/3.1.0 pkginfo/1.5.0.1 requests/2.22.0 setuptools/41.2.0 requests-toolbelt/0.9.1 tqdm/4.39.0 CPython/3.8.0
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