BIBLIOGRAPHY

  • Igual, Laura, Seguí, Santi, Introduction to Data Science: A Python Approach to Concepts, Techniques and Applications, Springer Verlag, 2017 DOI 10.1007/978-3-319-50017-1
  • Chen, Li M., Su, Zhixun, Jiang, Bo, Mathematical Problems in Data Science: Theoretical and Practical Methods, Springer, 2015, DOI 10.1007/978-3-319-25127-1
  • Steele, Brian, Chandler, John, Reddy, Swarna, Algorithms for Data Science, Springer, 2016, DOI 10.1007/978-3-319-45797-0
  • Akerkar, Rajendra, Sajja, Priti Srinivas, Intelligent Techniques for Data Science Springer, 2016, DOI 10.1007/978-3-319-29206-9
  • Runkler, Thomas A., Data Analytics, Models and Algorithms for Intelligent Data Analysis, Springer, 2016 DOI 10.1007/978-3-658-14075-5
  • Albert-László Barabási, Márton Pósfai, Network Science, Cambridge University Press, 2016

Interesting references

  • Liu, L. and Özsu, M.T., 2019. Encyclopedia of database systems. New York, NY, USA:: Springer. https://drive.google.com/file/d/1ZvoL8PgJf1SB6hdFrcft0F6ab63mFh1Y/view

Useful cheat sheets

  • SQL Cheat Sheet
  • Python for Data Analytics Cheat Sheets