Alternatives and similar repositories for model_interpretability_post

Users that are interested in model_interpretability_post are comparing it to the libraries listed below

• docker-for-data-science / docker-for-data-science-tutorial
  Materials for "Docker for Data Science" tutorial presented at PyCon 2018 in Cleveland, OH
  ☆156Updated 4 years ago
• mnguyenngo / ab-framework
  Notes and Python scripts for A/B or Split Testing
  ☆142Updated 3 years ago
• jem1031 / pandas-pipelines-custom-transformers
  Material for Talk at PyData Seattle 2017
  ☆168Updated 7 years ago
• alteryx / predict-customer-churn
  A general-purpose framework for solving problems with machine learning applied to predicting customer churn
  ☆418Updated last year
• tkrabel / edaviz
  edaviz - Python library for Exploratory Data Analysis and Visualization in Jupyter Notebook or Jupyter Lab
  ☆225Updated 5 years ago
• harnav / pydata-docker-tutorial
  Tutorial given at PyData LA 2018
  ☆97Updated last year
• Soluto / python-flask-sklearn-docker-template
  A simple example of python api for real time machine learning, using scikit-learn, Flask and Docker
  ☆136Updated 2 years ago
• bgweber / DS_Production
  ☆155Updated 4 years ago
• j-planet / machine-learning-big-loop
  a big loop that runs through all sklearn supervised models, as well as hyperparameter-selection via cross-validation
  ☆36Updated 8 years ago
• FilippoBovo / production-data-science
  Production Data Science: a workflow for collaborative data science aimed at production
  ☆454Updated 5 years ago
• nicolasfauchereau / Auckland_Cycling
  An analysis of cycling counts in Auckland in relation to the weather
  ☆88Updated 2 years ago
• jphall663 / interpretable_machine_learning_with_python
  Examples of techniques for training interpretable ML models, explaining ML models, and debugging ML models for accuracy, discrimination, …
  ☆682Updated last year
• Sundar0989 / WOE-and-IV
  ☆136Updated 6 years ago
• d6t / d6t-python
  Accelerate data science
  ☆116Updated 4 years ago
• htorrence / pytest_examples
  Reference package for unit tests
  ☆49Updated 6 years ago
• klemag / pydata_nyc2018-intro-to-model-interpretability
  Notebook and slides for my talk at Pydata NYC 2018
  ☆88Updated last year
• h2oai / mli-resources
  H2O.ai Machine Learning Interpretability Resources
  ☆489Updated 4 years ago
• chrisluedtke / data-science-journal
  Personal repository of data science demonstrations and references
  ☆77Updated 2 years ago
• dziganto / Data_Science_Fundamentals
  ☆101Updated 7 years ago
• kjam / data-cleaning-101
  Data Cleaning Libraries with Python
  ☆289Updated 2 years ago
• chrispaulca / waterfall
  An easy to use waterfall chart function for Python
  ☆162Updated 4 years ago
• jphall663 / GWU_data_mining
  Materials for GWU DNSC 6279 and DNSC 6290.
  ☆240Updated 4 months ago
• jbwhit / jupyter-tips-and-tricks
  Using Project Jupyter for data science.
  ☆259Updated 4 years ago
• sosuneko / pydqc
  python automatic data quality check toolkit
  ☆282Updated 5 years ago
• dabl / dabl
  Data Analysis Baseline Library
  ☆728Updated 9 months ago
• hgrif / example-project
  Example Python DS project
  ☆71Updated 7 years ago
• alteryx / open_source_demos
  A collection of demos showcasing automated feature engineering and machine learning in diverse use cases
  ☆501Updated 2 years ago
• knathanieltucker / deep-learning-building-blocks
  ☆33Updated 2 years ago
• BigDataRepublic / bdr-analytics-py
  Common data science and data engineering utilities to help us perform analytics. Our toolbox for data scientists, licensed under Apache-2…
  ☆30Updated 7 years ago
• bhargavvader / personal
  Contains Jupyter Notebooks of stuff I am working on.
  ☆197Updated 5 years ago