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Linear Regression with numpy only.

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PyPI version numpy-linreg Total alerts Language grade: Python deepcode


Linear Regression with numpy only.


The numpy-linreg git repo is available as PyPi package

pip install numpy-linreg
pip install git+ssh://


Ridge Regression

import numpy_linreg.ridge as ridge
import numpy_linreg.metrics as metrics
beta =, X)
rmse = metrics.rmse(y, X, beta)

OLS Regression

import numpy_linreg.ols as ols
beta =, X)
beta = ols.pinv(y, X)
beta = ols.qr(y, X)
beta = ols.svd(y, X)

Check the examples folder for notebooks.



Install a virtual environment

python3.6 -m venv .venv
source .venv/bin/activate
pip3 install --upgrade pip
pip3 install -r requirements.txt
pip3 install -r requirements-dev.txt
pip3 install -r requirements-demo.txt

(If your git repo is stored in a folder with whitespaces, then don’t use the subfolder .venv. Use an absolute path without whitespaces.)

Python commands

  • Jupyter for the examples: jupyter lab

  • Check syntax: flake8 --ignore=F401 --exclude=$(grep -v '^#' .gitignore | xargs | sed -e 's/ /,/g')


pandoc --from markdown --to rst -s -o README.rst
python sdist
twine upload -r pypi dist/*

Clean up

find . -type f -name "*.pyc" | xargs rm
find . -type d -name "__pycache__" | xargs rm -r
rm -r .pytest_cache
rm -r .venv


Please open an issue for support.


Please contribute using Github Flow. Create a branch, add commits, and open a pull request.

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numpy-linreg-0.1.2.tar.gz (8.2 kB view hashes)

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