I am sharing a new free video where I work through a great common argument that bounds expected excess generalization error as a ratio of model complexity (in rows) over training set size (again in rows), independent of problem dimension.

(link)

For more of my notes on support vector machines style learning, please see here and here.

Categories: Pragmatic Data Science Tutorials

Tagged as: data science Machine Learning Practical Data Science Pragmatic Machine Learning pydata R Statistics

jmount

Data Scientist and trainer at Win Vector LLC. One of the authors of Practical Data Science with R.