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 - How does reinforcement learning work? Explain agent, environment, reward and policy.
An agent takes actions in an environment, receives a reward and a new state, and learns a policy (a rule for choosing actions) that maximises total reward over time. It learns by trial and error, not from labelled examples.
BeginnerQuick answer1 min read