he multiple-choice questions covered precision and recall calculations, the differences between bagging and boosting, overfitting-related concepts, and manual forward/backward propagation calculations for neural networks. However, the programming section was highly restrictive. We were limited to using scipy.cdist for KNN and sklearn.tree.DecisionTreeClassifier for decision trees. As a result, I spent the majority of the time checking the documentation. I could not understand the restriction on NumPy, as many of my standard NumPy operations were unavailable, and I couldn't come up with alternatives under the time pressure. Consequently, I left the final three problems incomplete.

2 leetcode easy-medium questions, and some general ML questions like AUC, overfitting.