Portfolio optimization with deep learning
1 maintainer
Metadata
1 maintainer
Release files for deepdow 0.2.3
For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.
Source distribution (sdist)
| File | Size | Uploaded | Provenance | |
|---|---|---|---|---|
| deepdow-0.2.3.tar.gz | 63.8 kB | Without provenance | Details |
Built distribution (wheel)
| File | Interpreter | ABI | Platform | Reset |
|---|---|---|---|---|
| deepdow-0.2.3-py3-none-any.whl | Python 3 | none | any | Details |
Total release size: 118.1 kB
Release files / deepdow-0.2.3.tar.gz
| Download URL | deepdow-0.2.3.tar.gz |
|---|---|
| Size | 63.8 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 | |
|
Uploaded using Trusted Publishing? What is trusted publishing? |
No |
| Uploaded via |
twine/4.0.2 CPython/3.10.8
|
Release files / deepdow-0.2.3-py3-none-any.whl
| Download URL | deepdow-0.2.3-py3-none-any.whl |
|---|---|
| Size | 54.4 kB |
| Tags | Python 3 |
|
SHA-256 checksum How to use checksums |
4395fa147a07c9b96affafa2c2e8c940053ec8224e6f4a6eefad6d3946c72087
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|
BLAKE2b-256 checksum How to use checksums |
2222d814e0488c35ecbaad0539a1f65657d15bf534b454e88c2134725aaf28a8
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| Upload date | |
|
Uploaded using Trusted Publishing? What is trusted publishing? |
No |
| Uploaded via |
twine/4.0.2 CPython/3.10.8
|
Security for deepdow 0.2.3
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No provenance found
None of the files in this release were uploaded with provenance metadata.
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