Data Science

Last updated Mar 28, 2023 Edit Source

Data science is an interdisciplinary field that uses scientific methods, processes, algorithms and systems to extract knowledge and insights from noisy, structured and unstructured data, and apply knowledge and actionable insights from data across a broad range of application domains

• https://en.wikipedia.org/wiki/Data_science
• https://github.com/bulutyazilim/awesome-datascience
• Reproducible Data Analysis in Jupyter (Vanderplas)
• Cookiecutter Data Science
• An Executive’s Guide To Understanding Cloud-based ML Services
• Why data-driven science is more than just a buzzword
• A Complete Data Science Curriculum for Beginners

• Cheat Sheets for Machine Learning and Data Science
• https://github.com/ml874/Data-Science-Cheatsheet
• https://github.com/aaronwangy/Data-Science-Cheatsheet
• https://github.com/FavioVazquez/ds-cheatsheets

• Data Never Sleeps 3.0
• The Data Science Industry - who does what
• Learn data science infographic
• DS Infographic
• Data Science Venn Diagram v2.0
• Updated DS Venn diagram
• DS vs STATS vs DATA-ENG

• See AI4G/AI4good

• #PAPER Science and data science (Blei 2017)
• #PAPER 50 Years of Data Science (Donoho 2017)
  • #TALK 50 Years of Data Science (Donoho)
    • https://www.youtube.com/watch?v=GUFL-Mf0EWY
    • https://www.youtube.com/watch?v=E7w-gfFKPf8
    • https://www.youtube.com/watch?v=QTzNXYcZLbU
    • https://www.youtube.com/watch?v=BnRRwmeGBgU
  • Comments:
    • https://matloff.wordpress.com/2016/01/23/some-comments-on-donahos-50-years-of-data-science/
    • https://medium.com/@srowen/what-50-years-of-data-science-leaves-out-2366c9b61d3d
    • https://www.youtube.com/watch?v=zamQgXDytUA
    • #TALK Big Data LDN 2016: What “50 Years of Data Science” Leaves Out
• #PAPER Theory-guided data science: a new paradigm for scientific discovery from data (Karpatne 2017)

• #BOOK Network Data Science (Johns Hopkins University 2022)
• #BOOK The Data Science Interview Book (2021)
• #BOOK R Programming for Data Science (Peng, 2020)
• #BOOK Statistical Inference via Data Science (Ismay 2020)
• #BOOK Data Science Live Book (Casas 2020)
• #BOOK Geographic Data Science with Python
  • See AI4ES/Geospatial science
• #BOOK Introduction to Data Science, Data Analysis and Prediction Algorithms with R (Irizarry 2019)
• #BOOK Data Science Live Book – in R (Casas 2019))
• #BOOK Python Programming for Data Science (Beuzen 2019)
• #BOOK Python for Data Analysis 2nd ed (McKinney, 2017 O’REILLY)
  • https://github.com/wesm/pydata-book
• #BOOK R for Data Science (Grolemund 2017 O’REILLY)
• #BOOK Scala: Guide for Data Science Professionals (Nicolas, 2017 PACKT)
• #BOOK Going pro in data science (Overton 2016, O’REILLY)
  • http://ds4100.weebly.com/uploads/8/6/5/9/8659576/going-pro-in-data-science.pdf
• #BOOK Weapons of Math Destruction - How big data increases inequality and threatens democracy (O’Neil, 2016)
  • https://we.riseup.net/assets/404114/Weapons+of+Math+Destruction+Cathy+O%27Neil.pdf
• #BOOK Introducing Data Science - Big Data, ML and more, using Python tools (Cielen 2016, MANNING)
  • http://bedford-computing.co.uk/learning/wp-content/uploads/2016/09/introducing-data-science-machine-learning-python.pdf
• #BOOK Mastering Python for Data Science (Madhavan 2015, PACKT)
  • http://nuovolabs.fauser.edu/~valeria/materiale-didattico/python/Packt.Mastering.Aug.2015.ISBN.1784390151.pdf
• #BOOK Python Data Science Handbook (VanderPlas, 2016 OREILLY)
  • http://nbviewer.jupyter.org/github/jakevdp/PythonDataScienceHandbook/blob/master/notebooks/Index.ipynb
• #BOOK Scala for Data Science (Bugnion, 2016 PACKT)
• #BOOK The field guide to DS (Booz Allen Hamilton Inc 2015)
  • https://www.boozallen.com/content/dam/boozallen_site/sig/pdf/publications/2015-field-guide-to-data-science.pdf
  • https://github.com/booz-allen-hamilton/The-Field-Guide-to-Data-Science

• #COURSE Introduction to Computational Thinking (MIT)
  • Fall 2020
  • Spring 2021
  • Using Julia
  • CS, Math, ML and applications (image processing, climate modelling/change)
• #COURSE Mathematical Tools for Data Science (NYU Center for Data Science)
• • #COURSE Python for Data Science workshop (Paris-Saclay Center for Data Science)
• #COURSE Data Science (Harvard CS109)
• #COURSE Data 8: The Foundations of Data Science (UC Berkeley)
  • https://www.inferentialthinking.com/index.html
• #COURSE Intro to Data Science (Udacity)
• #COURSE Introduction to Data Science in Python (Coursera, U Michigan)
• #COURSE Data Science in Stratified Healthcare and Precision Medicine (Coursera, U Edinburgh)
• #COURSE Big Data Analytics in Healthcare (Udacity, Georgia Tech)
• #TALK Building a Data Science Team with Open Source Tools
• #TALK Introduction to Python for Data Science (Seabold, PyCon 2018)

• #CODE Jupyter
• #CODE Zepelin
• #CODE Rstudio
• #CODE Cauldron
  • http://www.unnotebook.com/
• #CODE Polynote
  • https://polynote.org/

• Google Colaboratory
• Binder
• Cocal
• Replit
• Deepnote

See AI/Math and Statistics/Math and Statistics

See AI/ML

See AI/DS and DataEng/Data engineering and computer science

See AI/DS and DataEng/Visualization