Neither. The values he gives are reasonable (not bad choices) but also quite broad (covering several orders of magnitude usually - not valuable per-se). Of cou

Neither. The values he gives are reasonable (not bad choices) but also quite broad (covering several orders of magnitude usually - not valuable per-se). Of course, things become much clearer when you actually know what the hyperparameters represent. For example, knowing the random forest algorithm, you'd know that having a higher number of estimators is always better (with the downside being diminishing returns and slower performance / more memory usage). Ironically, the blog post here gets this point wrong.