Essential Readings in Data Science
What is considered canon?
Data Science Literature Review
I saw an intriguing question posed on Twitter and some of the responses were illuminating.
Here’s another variant of the question:
Although Data Science has a long history, it’s considered a relatively young field.
This space will be used to document recommended reading for new entrants:

Downey, Allen (2016) There is only one test. source

Wickham, Hadley (2014) Tidy Data. The Journal of Statistical Software, vol 59. original, update

James, G., Witten, D., Hastie, T. & Tibshirani, R. (2014) An Introduction to Statistical Learning with Applications in R. source

Shmueli, G. (2010) To explain or to predict? Statistical Science, 25(3), 289310. source

Hernan, M.A., Hsu, J. & Healy, B. (2019) A second chance to get causal inference right: A classification of Data Science tasks. Chance, vol 32(1). source

Gelman, A., Pasarica, C. & Dodhia, R. (2002) Let’s practice what we preach: Turning tables into graphs. The American Statistician, vol 56(2). source

Scott FormannRoe (June, 2012) Understanding the BiasVariance Tradeoff. source

Donoho, D (2017) 50 Years of Data Science. Journal of Computational and Graphical Statistics, vol 26(4). source

Wilson, G., Bryan, J., Cranston, K., Kitzes, J., Nederbragt, L. & Teal, T.K. (2017) Good enough practices in scientific computing. Plos Computational Biology. source

Kevin Markham (2019) 100 pandas tricks to save you time and energy. source

Chris Albon’s code snippets. source

Howard, J. & Gugger, S. (Aug 4, 2020) Deep Learning for Coders with fastai and PyTorch: AI Applications without a PhD 1st Ed. source

Brandon Rohrer (Jan, 2020) EndtoEnd Machine Learning: Complete Course Catalog. source; second source

John Rauser (Dec, 2016) How Humans See Data youtube

Broman, K.W. & Woo, K.H. (2018) Data Organization in Spreadsheets. The American Statistician, vol 72(1). source

Sculley, D., Holt, G., Golovin, D., Davydov, E., Phillips, T., Ebner, D., Chaudhary, V., & Young, M. (2014) Machine Learning: The High Interest Credit Card of Technical Debt. source

3Blue1Brown for Linear Algebra youtube

Jenny Bryan. Stat 545: Data Wrangling, Exploration and Analysis with R. source