Rapid Deep Neural Networks
Project description
radnn - Rapid Deep Neural Networks
A library that brings the Rapid Application Development (RAD) approach into the lifecycle of Deep Learning models. Adapts objects from other frameworks and hides their implementation details to put emphasis on:
- Experiments: Data, Models, Training, Reproducibility
- Management: Process, Storage, Deployment
- Evaluation: Metrics, Plots, Visualizations
- Integration: IPC, Web API
Release history Release notifications | RSS feed
Download files
Download the file for your platform. If you're not sure which to choose, learn more about installing packages.
Source Distribution
radnn-0.0.3.tar.gz
(10.8 kB
view details)
Built Distribution
Filter files by name, interpreter, ABI, and platform.
If you're not sure about the file name format, learn more about wheel file names.
Copy a direct link to the current filters
radnn-0.0.3-py3-none-any.whl
(19.1 kB
view details)
File details
Details for the file radnn-0.0.3.tar.gz.
File metadata
- Download URL: radnn-0.0.3.tar.gz
- Upload date:
- Size: 10.8 kB
- Tags: Source
- Uploaded using Trusted Publishing? No
- Uploaded via: twine/6.1.0 CPython/3.11.8
File hashes
| Algorithm | Hash digest | |
|---|---|---|
| SHA256 |
9411dc31f64569c83037a904682f971e5781992da4a8629dc6056719a77542ed
|
|
| MD5 |
6b0e721e88783e83bc95fa48055cfdfc
|
|
| BLAKE2b-256 |
6430403b98b242d4542c83dbf1f6cca1eb6504135f6526660708fbbb44e9e0eb
|
File details
Details for the file radnn-0.0.3-py3-none-any.whl.
File metadata
- Download URL: radnn-0.0.3-py3-none-any.whl
- Upload date:
- Size: 19.1 kB
- Tags: Python 3
- Uploaded using Trusted Publishing? No
- Uploaded via: twine/6.1.0 CPython/3.11.8
File hashes
| Algorithm | Hash digest | |
|---|---|---|
| SHA256 |
df670eaff61ee126fb9204129c8ab55af8e7c29dab55a2e1d514362626e147ac
|
|
| MD5 |
18aa106bb970df3492b2bffa52aadb62
|
|
| BLAKE2b-256 |
3cfcfa9ff2f9f1639e54aff6dc9389f4769f4a100825271ef5515555958da0d0
|
