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 do the C and gamma parameters do in an RBF SVM?
C controls how much misclassification is tolerated: high C fits training data tightly (risk overfitting), low C allows a wider, smoother margin. Gamma sets how far one point's influence reaches: high gamma gives wiggly, local boundaries, low gamma gives smooth ones.
IntermediateQuick answer1 min read - Which hyperparameters matter most in a random forest?
n_estimators (more trees gives stable results with diminishing returns), max_features (how many features each split considers), max_depth, min_samples_leaf and min_samples_split. max_features and min_samples_leaf usually matter most.
IntermediateQuick answer1 min read