Alternatives and similar repositories for awesome-datascience

Users that are interested in awesome-datascience are comparing it to the libraries listed below

• tdpetrou / Book-Reviews
  ☆26Updated 7 years ago
• Acrotrend / Awesome-Customer-Analytics
  A curated list of awesome customer analytics content
  ☆98Updated 7 years ago
• martinapugliese / tales-science-data
  WORK UNDER RESTRUCTURING
  ☆41Updated 7 months ago
• amitkaps / art-data-science
  The Art of Data Science
  ☆36Updated 6 years ago
• GalvanizeDataScience / self-study-resources
  DSI Self Study Resources
  ☆18Updated 5 years ago
• wimlds / conferences
  List of Machine Learning & Data Science Conferences
  ☆82Updated 5 years ago
• KarrieK / pandas_data_cleaning
  A brief guide and tutorial on how to clean data using pandas and Jupyter notebook
  ☆42Updated last year
• jakevdp / JupyterWorkflow
  Reproducible Data Analysis Workflow in Jupyter
  ☆118Updated 7 years ago
• amitkaps / full-stack-data-science
  Full Stack Data Science in Python
  ☆256Updated 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
  ☆156Updated 4 years ago
• croach / statistics-for-hackers
  A Jupyter notebook to accompany Jake VanderPlas's "Statistics for Hackers" talk from PyCon 2016.
  ☆76Updated 7 years ago
• realpython / web-dev-for-data-scientists
  ☆52Updated 8 years ago
• ericmjl / data-testing-tutorial
  A short tutorial for data scientists on how to write tests for code + data.
  ☆120Updated 5 years ago
• kjam / data-cleaning-101
  Data Cleaning Libraries with Python
  ☆289Updated last year
• DeltaAnalytics / machine_learning_for_good
  Machine learning fundamentals lesson in interactive notebooks
  ☆179Updated 4 years ago
• unnati-xyz / intro-python-data-science
  Introduction to Data Science
  ☆17Updated 9 years ago
• tdpetrou / pandas_cub
  Learn how to build a data analysis library from scratch
  ☆204Updated 3 years ago
• datacamp / datacamp_facebook_live_titanic
  DataCamp Facebook Live Code Along Session 2: Learn how to complete a Kaggle competition using exploratory data analysis, data munging, da…
  ☆61Updated 5 years ago
• d6t / d6t-python
  Accelerate data science
  ☆116Updated 4 years ago
• khanhnamle1994 / applied-machine-learning
  A step-by-step guide to get started with Applied Machine Learning
  ☆140Updated 6 years ago
• DeltaAnalytics / machine_learning_resources
  Delta believes in building technical capacity all over the world. We believe that data is powerful, and that anybody should be able to ha…
  ☆25Updated 7 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 3 years ago
• robert8138 / deep-learning-deliberate-practice
  Deliberate Practice for Learning Deep Learning
  ☆111Updated 6 years ago
• algobeans / numsense
  Accompanying R scripts for tutorials in our new data science book, Numsense!
  ☆16Updated 8 years ago
• manifoldai / docker-cookiecutter-data-science
  A fork of the cookiecutter-data-science leveraging Docker for local development.
  ☆131Updated 5 years ago
• datacamp / datacamp_facebook_live_nlp
  DataCamp Facebook Live Code Along Session 1: Enjoy.
  ☆127Updated 7 years ago
• jbwhit / jupyter-tips-and-tricks
  Using Project Jupyter for data science.
  ☆259Updated 4 years ago
• trallard / airflow-tutorial
  🐍💨 Airflow tutorial for PyCon 2019
  ☆85Updated 2 years ago
• hgrif / example-project
  Example Python DS project
  ☆71Updated 7 years ago
• dataquestio / analytics_pipeline
  Code to build a simple analytics data pipeline with Python
  ☆102Updated 8 years ago