docker-for-data-science / docker-for-data-science-tutorial

Related projects ⓘ

Alternatives and complementary repositories for docker-for-data-science-tutorial

• harnav / pydata-docker-tutorial
  Tutorial given at PyData LA 2018
  ☆97Updated 3 months ago
• hackalog / bus_number
  Up Your Bus Number: A Primer for Reproducible Data Science
  ☆68Updated 5 years ago
• tdpetrou / integrating-pandas-with-scikit-learn
  Tutorial covering a new workflow available going from pandas to scikit-learn
  ☆40Updated last year
• ericmjl / data-testing-tutorial
  A short tutorial for data scientists on how to write tests for code + data.
  ☆117Updated 4 years ago
• DunderData / Tutorials
  Python data science and machine learning from Ted Petrou with Dunder Data
  ☆52Updated 2 years ago
• loldja / loldja.github.io
  Data science blog
  ☆33Updated 6 years ago
• hgrif / example-project
  Example Python DS project
  ☆71Updated 6 years ago
• chrispaulca / waterfall
  An easy to use waterfall chart function for Python
  ☆160Updated 3 years ago
• fonnesbeck / intro_stat_modeling_2017
  Introduction to Statistical Modeling with Python (PyCon 2017)
  ☆167Updated 4 years ago
• tklouie / PyData_LA_2018
  Added repo for PyData LA 2018 tutorial
  ☆88Updated 6 years ago
• datacamp / datacamp_facebook_live_dataframed
  DataCamp Facebook Live Code Along Session 4: Learn techniques that guests on the DataFramed podcast say are their favourite. Enjoy!
  ☆24Updated 6 years ago
• alysivji / talks
  Code, slides, and documentation for the talks I have given.
  ☆112Updated last year
• bgweber / DS_Production
  ☆155Updated 4 years ago
• bhargavvader / personal
  Contains Jupyter Notebooks of stuff I am working on.
  ☆199Updated 4 years ago
• jem1031 / pandas-pipelines-custom-transformers
  Material for Talk at PyData Seattle 2017
  ☆168Updated 6 years ago
• deniederhut / Pandas-Tutorial-SciPyConf-2018
  ☆48Updated 6 years ago
• klemag / PyconUS_2019-model-interpretability-tutorial
  Content for the Model Interpretability Tutorial at Pycon US 2019
  ☆41Updated 3 months ago
• gaganmanku96 / Docker-Tutorial---Data-Scientists
  ☆27Updated 4 years ago
• ikding / pycon_time_series
  PyCon 2017 tutorial on time series analysis
  ☆72Updated 7 years ago
• klemag / pydataLDN_2019-maintainable-code-for-data-science
  ☆47Updated 5 years ago
• WillKoehrsen / probabilistic-programming
  Experimenting with and teaching probabilistic programming
  ☆103Updated 2 years ago
• FilippoBovo / production-data-science
  Production Data Science: a workflow for collaborative data science aimed at production
  ☆454Updated 4 years ago
• trallard / airflow-tutorial
  🐍💨 Airflow tutorial for PyCon 2019
  ☆85Updated last year
• amueller / ml-workshop-4-of-4
  Advanced Machine Learning with Scikit-learn part II
  ☆162Updated 4 years ago
• WillKoehrsen / data-science-for-good
  Data Science for Good Projects
  ☆49Updated 6 years ago
• justmarkham / machine-learning-for-software-engineers
  A complete daily plan for studying to become a machine learning engineer.
  ☆50Updated 8 years ago
• alanderex / pydata-pandas-workshop
  Material for my PyData Jupyter & Pandas Workshops, I'm also available for personal in-house trainings on request
  ☆65Updated 2 years ago
• amueller / ml-training-advanced
  Materials for the "Advanced Scikit-learn" class in the afternoon
  ☆164Updated 5 years ago
• flavianh / dashboards-frameworks-comparison
  ☆76Updated 6 years ago