https://github.com/benhunter/machine-learning-pocket-reference

O'Reilly book by Matt Harrison. Working with Structured Data in Python
https://github.com/benhunter/machine-learning-pocket-reference

Last synced: 8 months ago
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O'Reilly book by Matt Harrison. Working with Structured Data in Python

• Host: GitHub
• URL: https://github.com/benhunter/machine-learning-pocket-reference
• Owner: benhunter
• License: mit
• Created: 2020-07-11T00:13:31.000Z (almost 6 years ago)
• Default Branch: master
• Last Pushed: 2022-12-08T10:28:46.000Z (over 3 years ago)
• Last Synced: 2025-03-30T01:35:00.777Z (about 1 year ago)
• Language: Jupyter Notebook
• Size: 386 KB
• Stars: 5
• Watchers: 3
• Forks: 1
• Open Issues: 10
• Metadata Files:
  • Readme: README.md
  • License: LICENSE

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README

          
# Machine-Learning-Pocket-Reference

O'Reilly book by Matt Harrison. Working with Structured Data in Python.

## Dataset

http://biostat.mc.vanderbilt.edu/wiki/pub/Main/DataSets/titanic3.xls

## Libraries

import autosklearn, catboost, category_encoders, dtreeviz, eli5, fancyimpute, fastai, featuretools, glmnet_py, graphviz, hdbscan, imblearn, janitor, lime, matplotlib, missingno, mlxtend, numpy, pandas, pdpbox, phate, pydotplus, rfpimp, scikitplot, scipy, seaborn, shap, sklearn, statsmodels, tpot, treeinterpreter, umap, xgbfir, xgboost, yellowbrick

pip install auto-sklearn catboost category_encoders dtreeviz eli5 fancyimpute fastai featuretools glmnet_py graphviz hdbscan imblearn pyjanitor lime matplotlib missingno mlxtend numpy pandas pdpbox phate pydotplus rfpimp scikit-plot scipy seaborn shap sklearn statsmodels tpot treeinterpreter umap-learn xgbfir xgboost yellowbrick