Math/Stat/ML/CS resources ordered by increasing prerequisite knowledge:
: Jon and Jerry's intro course on probability, Bayesian stats, and frequentist stats. Completely self-contained on OCW!
: Gil Strang's legendary linear algebra course.
: incredible podcast on machine learning by friends of the SMRC Ryan Adams and Katherine Gorman.
: intro to programming using Python.
: Ryan Adams' colloquium at Ó³»´«Ã½.
: go big or go home with pySpark in this archived BerkeleyX course.
: excellent 6-part series on Coursera from UCSD.
, Christopher Bishop. Bayesian treatment of ML.
, Trevor Hastie, Robert Tibshirani, Jerome Friedman. Both stats and ML.
, Kevin Murphy. Encyclopedic on ML.
, Rick Durrett: a standard reference on modern, measure-theoretic probability theory.
P1, P2, P3: problem sets from Alex's Harvard graduate course on the core concepts of modern, measure-theoretic probability theory.
Biology resources for computationalists:
: Eric Lander's introduction to biology!
, Horace Judson (1979): a masterpiece of history of science, covering the birth and development of molecular biology, based on interviews with over one hundred of the scientists who played key roles.
MPG primer videos: experts from across the Ó³»´«Ã½ give in-depth introductions to principals, data, and analysis underlying medical and population genetics.