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 the difference between supervised, unsupervised and reinforcement learning?
Supervised learning trains on examples that come with the correct answer (labels). Unsupervised learning finds patterns in data with no labels, such as groups. Reinforcement learning trains an agent by trial and error, using rewards and penalties from an environment.
BeginnerIn-depth4 min read - Give three real-world examples each of supervised and unsupervised learning.
Supervised: spam filtering, house price prediction, loan default prediction (all have known past answers). Unsupervised: customer segmentation, anomaly detection in UPI transactions, topic discovery in news articles (no answers given).
BeginnerQuick answer1 min read - What is the difference between classification and regression?
Classification predicts a category (spam or not spam, pass or fail). Regression predicts a continuous number (a house price, tomorrow's temperature). The choice depends on the type of the target column, not on the algorithm.
BeginnerQuick answer1 min read