Interview Q&A / Machine Learning
Machine Learning interview questions
Supervised vs unsupervised learning, overfitting, metrics and the classic models, explained simply.
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- What is overfitting and underfitting, and what is the bias-variance trade-off?
Overfitting means the model memorises the training data, including noise, so it does well in training but badly on new data. Underfitting means the model is too simple to learn the pattern at all. The bias-variance trade-off is the balance between these two errors.
BeginnerIn-depth4 min read - How do you stop a decision tree from overfitting?
Limit its growth (max_depth, min_samples_leaf, min_samples_split, max_leaf_nodes) or prune it afterwards with cost-complexity pruning (ccp_alpha). Choose the settings by cross-validation. Or use an ensemble such as a random forest.
BeginnerQuick answer1 min read