1. A nice blog on CS including learnings: https://blog.acolyer.org/ called “the morning paper”: an interesting/influential/important paper from the world of CS every weekday morning, as selected by Adrian Colyer. I hope there is a similar blog on Statistics, reviewing and recommending an interesting/influential/important paper from the world of Statistics.
  2. A wonderful summary of Mathematical Tricks Commonly Used in Machine Learning and Statistics with examples
  3. I just realized that when I teach ridge regression I should have used A Useful Matrix Inverse Equality for Ridge Regression
  4. GANs should be gained much attention in the stats community: Understanding Generative Adversarial Networks. This is a nice post about GANs based on “probably the highest-quality general overview available nowadays: Ian Goodfellow’s tutorial on arXiv, which he then presented in some form at NIPS 2016. “
  5. R or Python? Why not both? Using Anaconda Python within R with {reticulate}
  6. “A heatmap is basically a table that has colors in place of numbers. Colors correspond to the level of the measurement.”