A package to implement and extend the methods desribed in 'Omnidirectional Transfer for Quasilinear Lifelong Learning'
Project description
ProgLearn
ProgLearn (Progressive Learning) is a package for exploring and using progressive learning algorithms developed by the neurodata group.
- Installation Guide: http://proglearn.neurodata.io/install.html
- Documentation: http://proglearn.neurodata.io
- Tutorials: http://proglearn.neurodata.io/tutorials.html
- Source Code: http://proglearn.neurodata.io/reference/index.html
- Issues: https://github.com/neurodata/proglearn/issues
- Contribution Guide: http://proglearn.neurodata.io/contributing.html
Some system/package requirements:
- Python: 3.6+
- OS: All major platforms (Linux, macOS, Windows)
- Dependencies: tensorflow, scikit-learn, scipy, numpy, joblib
Project details
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
proglearn-0.0.7.tar.gz
(21.0 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
proglearn-0.0.7-py3-none-any.whl
(27.2 kB
view details)
File details
Details for the file proglearn-0.0.7.tar.gz.
File metadata
- Download URL: proglearn-0.0.7.tar.gz
- Upload date:
- Size: 21.0 kB
- Tags: Source
- Uploaded using Trusted Publishing? No
- Uploaded via: twine/3.4.2 importlib_metadata/4.8.1 pkginfo/1.7.1 requests/2.25.1 requests-toolbelt/0.9.1 tqdm/4.55.1 CPython/3.8.5
File hashes
| Algorithm | Hash digest | |
|---|---|---|
| SHA256 |
9354f300ccb1e7b9c5d771e553edb4c6866a94dbfb4220ef1227da11235b16ed
|
|
| MD5 |
b821be9f35d79502975ad1bc46ef69c2
|
|
| BLAKE2b-256 |
06bd8dd7ceea03602a50329657af661b8af4806bf78e48c5cc908c4e9b52e3c8
|
File details
Details for the file proglearn-0.0.7-py3-none-any.whl.
File metadata
- Download URL: proglearn-0.0.7-py3-none-any.whl
- Upload date:
- Size: 27.2 kB
- Tags: Python 3
- Uploaded using Trusted Publishing? No
- Uploaded via: twine/3.4.2 importlib_metadata/4.8.1 pkginfo/1.7.1 requests/2.25.1 requests-toolbelt/0.9.1 tqdm/4.55.1 CPython/3.8.5
File hashes
| Algorithm | Hash digest | |
|---|---|---|
| SHA256 |
c427e050a9d177339077679497ebcbe26e65b870b36877251b25ea562527e132
|
|
| MD5 |
1ede5660b9dbdf54b6e4c8228615e6d4
|
|
| BLAKE2b-256 |
afa3219ae8111f505bf12b98f76cd6ee48ef88c73a6cdeb49bcbe0498d95e98a
|