This repository is my project to bring velocity to deep-learning research, by providing tried and tested large pool of prebuilt components that are known to be working well together.
I would like to minimize time to market of new projects, ease experimentation and provide bits of experiment management to bring some order to the data science workflow.
Ideally, for most applications it should be enough to write a config file wiring existing components together. If that’s not the case writing bits of custom code shouldn’t be unnecessarily complex.
This repository is still in an early stage of that journey but it will grow as I’ll be putting some work into it.
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Release files for vel 0.3.0
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| File | Size | Uploaded | Provenance | Actions |
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| vel-0.3.0.tar.gz | 125.0 kB | Without provenance | Details for vel-0.3.0.tar.gz |
Release files / vel-0.3.0.tar.gz
| Download URL | vel-0.3.0.tar.gz |
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| Size | 125.0 kB |
| Tags | Source |
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SHA-256 checksum How to use checksums |
c6b8a3f99d364ffd20f40ca20acfd9a3188928b67543e7a2ee14f6dca695ba68
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twine/1.13.0 pkginfo/1.5.0.1 requests/2.21.0 setuptools/40.6.2 requests-toolbelt/0.9.1 tqdm/4.31.1 CPython/3.6.8
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Security for vel 0.3.0
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