Recently I finished reading the book Trustworthy Online Controlled Experiments, and here I put together my reading notes. The book has five parts. The first two parts are a high-level introduction of online controlled experiments. Why do we need to conduct controlled experiments? What is the evaluation metric for the experiments? The last three parts are more technically focused. The third part introduces some alternative methods when controlled experiments are not feasible.

In the past year, I started to pick up some optimization algorithms in work to solve problems like finding optimal prices to maximize business' profits with constraints. While memory is still fresh, I decided to write down my learning notes here. This is not an exhaustive survey of optimization algorithms, it only serves as the learning notes of the optimization algorithms which I have exposed so far. Optimization Overview There are different ways to categorize the optimization algorithm.