Metadata-Version: 2.1
Name: mlmachine
Version: 0.0.34
Summary: Accelerate machine learning experimentation
Home-page: https://github.com/petersontylerd/mlmachine
Maintainer: Tyler Peterson
Maintainer-email: petersontylerd@gmail.com
License: MIT
Project-URL: bug tracker, https://github.com/petersontylerd/mlmachine/issues
Project-URL: source code, https://github.com/petersontylerd/mlmachine
Keywords: machine learning,data science
Platform: UNKNOWN
Classifier: Development Status :: 3 - Alpha
Classifier: Intended Audience :: Developers
Classifier: Intended Audience :: Science/Research
Classifier: Topic :: Scientific/Engineering
Classifier: Topic :: Scientific/Engineering :: Artificial Intelligence
Classifier: Topic :: Scientific/Engineering :: Information Analysis
Classifier: Topic :: Scientific/Engineering :: Visualization
Classifier: Topic :: Software Development
Classifier: Topic :: Software Development :: Libraries :: Python Modules
Classifier: License :: OSI Approved :: MIT License
Classifier: Programming Language :: Python :: 3
Classifier: Operating System :: OS Independent
Requires-Python: >=3.6.1
Requires-Dist: catboost (>=0.21)
Requires-Dist: hyperopt (>=0.2.3)
Requires-Dist: lightgbm (>=2.3.1)
Requires-Dist: matplotlib (>=3.1.3)
Requires-Dist: numpy (>=1.18.1)
Requires-Dist: pandas (>=1.0.1)
Requires-Dist: prettierplot (>=0.0.3)
Requires-Dist: seaborn (>=0.10.0)
Requires-Dist: scikit-learn (>=0.22.1)
Requires-Dist: scipy (>=1.4.1)
Requires-Dist: shap (>=0.34.0)
Requires-Dist: statsmodels (>=0.11.0)
Requires-Dist: xgboost (>=0.90)

# mlmachine

mlmachine accelerates the end-to-end machine learning pipeline.

This library is for those who have...

...copied a well-worn block of code and painstakingly adapted it to a new problem.
...wished it wasn't so tedious to perform exploratory data analysis.


mlmachine stands in the shoulders of these great packages:


[catboost](https://github.com/catboost/catboost) | [eif](https://github.com/sahandha/eif) | [hyperopt](https://github.com/hyperopt/hyperopt) | [imbalanced-learn](https://github.com/scikit-learn-contrib/imbalanced-learn) | [jupyter](https://github.com/jupyter/notebook) | [lightgbm](https://github.com/microsoft/LightGBM) | [matplotlib](https://github.com/matplotlib/matplotlib) | [numpy](https://github.com/numpy/numpy) | [pandas](https://github.com/pandas-dev/pandas) | [prettierplot](https://github.com/petersontylerd/prettierplot) | [scikit-learn](https://github.com/scikit-learn/scikit-learn) | [scipy](https://github.com/scipy/scipy) | [seaborn](https://github.com/mwaskom/seaborn) | [shap](https://github.com/slundberg/shap) | [statsmodels](https://github.com/statsmodels/statsmodels) | [xgboost](https://github.com/dmlc/xgboost) |

