Powerful machine learning utilities for python
Project description
# omni-learn
This repo contains a framework for various machine learning and simulation projects.
## Installation
Run pip install . while in this dir to install package.
### Environment Variables
It is strongly encouraged to set a few environment variables when using this library:
OMNILEARN_SAVE_DIR=”$HOME/trained_nets” - set this to an absolute path to a directory you have write access to, this is where scripts will save output (by default).
OMNILEARN_DATA_DIR=”$HOME/local_data” - set this to an absolute path to a directory with some datasets (best to also have write access to allow automatic downloading of some datasets).
## Execution
For an example of how to use this library, see the mnist/ dir.
An example execution from inside the mnist/ dir (requires the environment variables above to be set):
python project.py model –name test-mnist
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
File details
Details for the file omnilearn-0.5.14.tar.gz
.
File metadata
- Download URL: omnilearn-0.5.14.tar.gz
- Upload date:
- Size: 130.1 kB
- Tags: Source
- Uploaded using Trusted Publishing? No
- Uploaded via: twine/3.4.2 importlib_metadata/4.6.3 pkginfo/1.7.1 requests/2.26.0 requests-toolbelt/0.9.1 tqdm/4.62.0 CPython/3.6.13
File hashes
Algorithm | Hash digest | |
---|---|---|
SHA256 | 55bf876eb9138d1bdea5f7dc4d243e77f60e69dbf15c56be4aa361827f10292f |
|
MD5 | 8b6f774a30eaa72eef803f5dbd565493 |
|
BLAKE2b-256 | 97692f4a26feb0896267c399482b4c5b9213998285989d8e5acefce48c8719a5 |