TO READ

Data Centric Sciences

  1. G. Vargas-solar, “Efficient data management for putting forward data centric sciences,” in Proc. 1st Int Workshop on Data Science: Methodologies and Use-Cases (DaS’17) (in press), 2017. [PDF]

Data Science Pipelines

  • G. Vargas-Solar, Enacting challenges of data science pipelines, https://medium.com/learning-based-data-science-pipelines-for-setting/enacting-challenges-of-data-science-pipelines-50685f168ad6
  • G. Vargas-Solar, Designing and enacting data science pipelines as queries, https://medium.com/@genovevavargassolar/designing-and-enacting-data-science-pipelines-as-queries-8e12bccea4e7
  • G. Vargas-Solar, From Data Management Systems to Data Science Environments: State of the Art, https://medium.com/@genovevavargassolar/from-data-management-systems-to-data-science-environments-state-of-the-art-fe8cd52481fc
  • G. Vargas-Solar, Challenges and issues to deal with a brand new type of queries: data science queries, https://medium.com/learning-based-data-science-pipelines-for-setting/challenges-and-issues-to-deal-with-a-brand-new-type-of-queries-data-science-queries-7163e9b365ed

Developing Data Engineering Skills

  • Data Engineering Cookbook, https://github.com/andkret/Cookbook
  • Probability Distributions in Data Science, https://towardsdatascience.com/probability-distributions-in-data-science-cce6e64873a7
  • Mathematics for Machine Learning, https://mml-book.github.io/book/mml-book.pdf

Useful cheat sheets

  • SQL Cheat Sheet
  • Python for Data Analytics Cheat Sheets

Data science cheat sheet [PDF]