AI & ML · Machine Learning Math

Information theory

98 problems in this skill, each with a solver-verified answer key. Answers are checked the moment you submit — with a hint if you want one and a worked solution afterwards.

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A few statements from this skill. Answers, hints and worked solutions live in the practice session.

Warm-up
A classifier's label variable $X$ is uniform over $2^{4}$ equally likely classes. Compute the entropy $H(X) = \sum_i p_i \log_2(1/p_i)$ in bits.
Warm-up
A classifier's label variable $X$ is uniform over $2^{5}$ equally likely classes. Compute the entropy $H(X) = \sum_i p_i \log_2(1/p_i)$ in bits.
Warm-up
A classifier's label variable $X$ is uniform over $2^{6}$ equally likely classes. Compute the entropy $H(X) = \sum_i p_i \log_2(1/p_i)$ in bits.

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