Python Machine Learning Utilities
Project description
pymlutil
Python Machine Learning utilities:
functions
GaussianBasis
Computes a unit height gaussian bell curve function
$ GaussianBasis(x, zero, sigma) = e^{-\frac{(x-zero)^2}{2*sigma^2}} $ \
- x : function input
- zero : location of the peak center
- sigma: curve with or standard deviation
def GaussianBasis(x, zero=0.0, sigma=0.33)
Example:
x = np.arange(-2.0, 2.0, 0.01)
y = GaussianBasis(torch.tensor(x))
plt.plot(x, y)
plt.show()
imutial
jsonutil
metrics
s3
torch_util
version
workflow
Packaging Python Projects How to Publish an Open-Source Python Package to PyPI
-
Install twine:
pip3 install twine
-
Build whl:
py setup.py sdist bdist_wheel
-
Upload package to pipy
twine upload dist/*
-
Load package into project
pip3 install --upgrade pymlutil
-
Include pymlutil into project
from pymlutil import *
Notes
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
pymlutil-0.0.47.tar.gz
(13.2 kB
view details)
Built Distribution
pymlutil-0.0.47-py3-none-any.whl
(18.1 kB
view details)
File details
Details for the file pymlutil-0.0.47.tar.gz
.
File metadata
- Download URL: pymlutil-0.0.47.tar.gz
- Upload date:
- Size: 13.2 kB
- Tags: Source
- Uploaded using Trusted Publishing? No
- Uploaded via: twine/3.8.0 pkginfo/1.8.2 readme-renderer/34.0 requests/2.27.1 requests-toolbelt/0.9.1 urllib3/1.26.9 tqdm/4.62.2 importlib-metadata/4.8.2 keyring/18.0.1 rfc3986/2.0.0 colorama/0.4.3 CPython/3.8.10
File hashes
Algorithm | Hash digest | |
---|---|---|
SHA256 | 8a7ca2c4d14f7ab88b12460328528a223e55e80e4eb7ad24edfaf7f2e92320b8 |
|
MD5 | 89a85cd834becee84922f1af89478527 |
|
BLAKE2b-256 | 0ecd969ebb3ec6d31f4ba5a5e72f715aec8ac98fe3577ef0ab1ad203f17e3efe |
File details
Details for the file pymlutil-0.0.47-py3-none-any.whl
.
File metadata
- Download URL: pymlutil-0.0.47-py3-none-any.whl
- Upload date:
- Size: 18.1 kB
- Tags: Python 3
- Uploaded using Trusted Publishing? No
- Uploaded via: twine/3.8.0 pkginfo/1.8.2 readme-renderer/34.0 requests/2.27.1 requests-toolbelt/0.9.1 urllib3/1.26.9 tqdm/4.62.2 importlib-metadata/4.8.2 keyring/18.0.1 rfc3986/2.0.0 colorama/0.4.3 CPython/3.8.10
File hashes
Algorithm | Hash digest | |
---|---|---|
SHA256 | b38e80eb34d15684259eb3b7c770fdace74d475b099b9c34869f2f14cd8955e4 |
|
MD5 | e3cde4c21dba62902acea846f698e242 |
|
BLAKE2b-256 | d7f90aed76ecd3131e7abc806118ce3957b27e0646a18ba662749169f30cbd09 |