Alternatives and similar repositories for DS_Production

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

• amueller / ml-workshop-4-of-4
  Advanced Machine Learning with Scikit-learn part II
  ☆163Updated 5 years ago
• amueller / ml-workshop-3-of-4
  Advanced Machine Learning with Scikit-learn part I
  ☆143Updated 5 years ago
• jem1031 / pandas-pipelines-custom-transformers
  Material for Talk at PyData Seattle 2017
  ☆168Updated 7 years ago
• harnav / pydata-docker-tutorial
  Tutorial given at PyData LA 2018
  ☆97Updated last year
• amueller / ml-workshop-1-of-4
  Introduction to Machine learning with Python, 4h interactive workshop
  ☆312Updated 5 years ago
• dziganto / Data_Science_Fundamentals
  ☆101Updated 7 years ago
• amueller / ml-workshop-2-of-4
  Intermediate Machine Learning with Scikit-learn, 4h interactive workshop
  ☆128Updated 4 years ago
• ericmjl / data-testing-tutorial
  A short tutorial for data scientists on how to write tests for code + data.
  ☆121Updated 5 years ago
• WillKoehrsen / probabilistic-programming
  Experimenting with and teaching probabilistic programming
  ☆105Updated 3 years ago
• MaartenGr / ML-API
  Guide on creating an API for serving your ML model
  ☆66Updated 3 years ago
• bgweber / StartupDataScience
  ☆295Updated 6 years ago
• tkrabel / edaviz
  edaviz - Python library for Exploratory Data Analysis and Visualization in Jupyter Notebook or Jupyter Lab
  ☆225Updated 6 years ago
• EricSchles / datascience_book
  ☆134Updated last year
• DunderData / Tutorials
  Python data science and machine learning from Ted Petrou with Dunder Data
  ☆55Updated 3 years ago
• tklouie / PyData_LA_2018
  Added repo for PyData LA 2018 tutorial
  ☆88Updated 7 years ago
• whiteboxml / teaching-ml-in-production
  ☆53Updated 3 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
  ☆160Updated 5 years ago
• brohrer / academic_advisory
  Collected opinions and advice for academic programs focused on data science skills.
  ☆440Updated 5 years ago
• ikding / pycon_time_series
  PyCon 2017 tutorial on time series analysis
  ☆72Updated 8 years ago
• tdpetrou / pandas_cub
  Learn how to build a data analysis library from scratch
  ☆209Updated 3 years ago
• dipanjanS / data_science_for_all
  Code and resources for my blog and articles to share Data Science and AI knowledge and learnings with everyone
  ☆211Updated 6 years ago
• amueller / ml-training-advanced
  Materials for the "Advanced Scikit-learn" class in the afternoon
  ☆165Updated 7 years ago
• amueller / dabl
  Data Analysis Baseline Library
  ☆133Updated last year
• chrispaulca / waterfall
  An easy to use waterfall chart function for Python
  ☆164Updated 4 years ago
• FilippoBovo / production-data-science
  Production Data Science: a workflow for collaborative data science aimed at production
  ☆456Updated 5 years ago
• klemag / pydata_nyc2018-intro-to-model-interpretability
  Notebook and slides for my talk at Pydata NYC 2018
  ☆88Updated last year
• woobe / h2o_tutorials
  Slides and code examples for H2O tutorials at various events
  ☆56Updated 8 years ago
• EricSchles / drifter_ml
  A machine learning testing framework for sklearn and pandas. The goal is to help folks assess whether things have changed over time.
  ☆104Updated 4 years ago
• chrisluedtke / data-science-journal
  Personal repository of data science demonstrations and references
  ☆78Updated 3 years ago
• ryanmark1867 / deep_learning_for_structured_data
  Production repo to accompany Deep Learning with Structured Data book from Manning: https://www.manning.com/books/deep-learning-with-struc…
  ☆73Updated 4 years ago