Technical Interview Questions
Anyone who has used Spotify or shopped at Amazon will recognize a recommendation system: It’s an information filtering system that predicts what a user might want to hear or see based on choice patterns provided by the user. A recommendation system is a type of information filtering system that predicts the preferences or ratings that … Read more
Pruning is a technique in machine learning that reduces the size of decision trees. It reduces the complexity of the final classifier, and hence improves predictive accuracy by the reduction of overfitting. Pruning can occur in: Top-down fashion. It will traverse nodes and trim subtrees starting at the root Bottom-up fashion. It will begin at … Read more
A decision tree builds classification (or regression) models as a tree structure, with datasets broken up into ever-smaller subsets while developing the decision tree, literally in a tree-like way with branches and nodes. Decision trees can handle both categorical and numerical data. In the context of a machine learning interview question, the correct answer to … Read more
Precision Precision is the ratio of several events you can correctly recall to the total number of events you recall (mix of correct and wrong recalls). Precision = (True Positive) / (True Positive + False Positive) Recall A recall is the ratio of a number of events you can recall the number of total events. … Read more
The bias-variance decomposition essentially decomposes the learning error from any algorithm by adding the bias, variance, and a bit of irreducible error due to noise in the underlying dataset. Necessarily, if you make the model more complex and add more variables, you’ll lose bias but gain variance. To get the optimally-reduced amount of error, you’ll … Read more