Alternatives and similar repositories for production-data-science

Users that are interested in production-data-science are comparing it to the libraries listed below

• jem1031 / pandas-pipelines-custom-transformers
  Material for Talk at PyData Seattle 2017
  ☆168Updated 7 years ago
• docker-for-data-science / docker-for-data-science-tutorial
  Materials for "Docker for Data Science" tutorial presented at PyCon 2018 in Cleveland, OH
  ☆154Updated 4 years ago
• bgweber / DS_Production
  ☆154Updated 4 years ago
• aajains / springboard-datascience-intensive
  ☆35Updated 7 years ago
• LeiG / Applied-Predictive-Modeling-with-Python
  A collection of notebook to learn the Applied Predictive Modeling using Python.
  ☆275Updated 8 years ago
• dabl / dabl
  Data Analysis Baseline Library
  ☆728Updated 5 months ago
• fonnesbeck / intro_stat_modeling_2017
  Introduction to Statistical Modeling with Python (PyCon 2017)
  ☆166Updated 4 years ago
• xLaszlo / datascience-fails
  Collection of articles listing reasons why data science projects fail.
  ☆464Updated 4 years ago
• alteryx / predict-customer-churn
  A general-purpose framework for solving problems with machine learning applied to predicting customer churn
  ☆412Updated 11 months ago
• ericmjl / data-testing-tutorial
  A short tutorial for data scientists on how to write tests for code + data.
  ☆120Updated 4 years ago
• robert8138 / python-deliberate-practice
  Deliberate Practice for Learning Python
  ☆548Updated last month
• tkrabel / edaviz
  edaviz - Python library for Exploratory Data Analysis and Visualization in Jupyter Notebook or Jupyter Lab
  ☆224Updated 5 years ago
• ericmjl / bayesian-stats-modelling-tutorial
  How to do Bayesian statistical modelling using numpy and PyMC3
  ☆665Updated 2 years ago
• mnguyenngo / ab-framework
  Notes and Python scripts for A/B or Split Testing
  ☆140Updated 2 years ago
• trainindata / testing-and-monitoring-ml-deployments
  Example project for the course "Testing & Monitoring Machine Learning Model Deployments"
  ☆135Updated last year
• drivendata / data-science-is-software
  ☆317Updated 4 years ago
• jbwhit / jupyter-tips-and-tricks
  Using Project Jupyter for data science.
  ☆258Updated 4 years ago
• loldja / loldja.github.io
  Data science blog
  ☆33Updated 6 years ago
• klemag / pydata_nyc2018-intro-to-model-interpretability
  Notebook and slides for my talk at Pydata NYC 2018
  ☆88Updated 11 months ago
• drivendataorg / box-plots-sklearn
  An implementation of some of the tools used by the winner of the box plots competition using scikit-learn.
  ☆299Updated 6 years ago
• JWarmenhoven / DBDA-python
  Doing Bayesian Data Analysis, 2nd Edition (Kruschke, 2015): Python/PyMC3 code
  ☆682Updated 3 years ago
• chrisluedtke / data-science-journal
  Personal repository of data science demonstrations and references
  ☆76Updated 2 years ago
• WillKoehrsen / probabilistic-programming
  Experimenting with and teaching probabilistic programming
  ☆104Updated 3 years ago
• matthewbrems / missing-data-workshop
  Matt Brems' Missing Data Workshop
  ☆83Updated 2 years ago
• MaxHalford / xam
  Personal data science and machine learning toolbox
  ☆365Updated 5 years ago
• brohrer / academic_advisory
  Collected opinions and advice for academic programs focused on data science skills.
  ☆443Updated 4 years ago
• amueller / dabl
  Data Analysis Baseline Library
  ☆132Updated 7 months ago
• chrispaulca / waterfall
  An easy to use waterfall chart function for Python
  ☆162Updated 4 years ago
• AllenDowney / BayesMadeSimple
  Code for a tutorial on Bayesian Statistics by Allen Downey.
  ☆352Updated 4 years ago
• harnav / pydata-docker-tutorial
  Tutorial given at PyData LA 2018
  ☆97Updated 9 months ago