machine-learning-my-way (early access)
Machine Learning My Way (MLMY) is a list of topics and selected links aimed at a technically curious, but non-expert reader. Topics include probability, statistics, econometrics, machine learning, neural nets, productisation, data quality, and business and social value of the above.
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Release files for mlmw 0.1.0
For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.
Source distribution (sdist)
| File | Size | Uploaded | Provenance | Actions |
|---|---|---|---|---|
| mlmw-0.1.0.tar.gz | 1.3 kB | Without provenance | Details for mlmw-0.1.0.tar.gz |
Built distribution (wheel)
| File | Interpreter | ABI | Platform | Actions Reset |
|---|---|---|---|---|
| mlmw-0.1.0-py3-none-any.whl | Python 3 | none | any | Details for mlmw-0.1.0-py3-none-any.whl |
Total release size: 2.9 kB
Release files / mlmw-0.1.0.tar.gz
| Download URL | mlmw-0.1.0.tar.gz |
|---|---|
| Size | 1.3 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 |
poetry/1.8.2 CPython/3.10.13 Linux/6.2.0-1019-azure
|
Release files / mlmw-0.1.0-py3-none-any.whl
| Download URL | mlmw-0.1.0-py3-none-any.whl |
|---|---|
| Size | 1.6 kB |
| Tags | Python 3 |
|
SHA-256 checksum How to use checksums |
1b720b1d8891c977cc8e3380a162d162a5e8dd0bf3ff0c1af120376fd909182e
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|
BLAKE2b-256 checksum How to use checksums |
4c04c2b1f386e87a3d576ed6472e48ef1073eaa4c9a2d1496d968c048378b0d2
|
| Upload date | |
|
Uploaded using Trusted Publishing? What is trusted publishing? |
No |
| Uploaded via |
poetry/1.8.2 CPython/3.10.13 Linux/6.2.0-1019-azure
|
Security for mlmw 0.1.0
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No provenance found
None of the files in this release were uploaded with provenance metadata.
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