Empirical Methods for Artificial Intelligence,
by Paul R. Cohen
Should I read this?
appears in Statistics.
This book presents empirical methods for studying complex computer programs: exploratory tools to help find patterns in data, experiment designs and hypothesistesting tools to help data speak convincingly, and modeling tools to help explain data.Computer science and Artificial Intelligence, in particular have no curriculum in research methods, as o...
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appears in Statistics.
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Not sure if this is the right fit?
Consider First Course in Probability, A by Sheldon Ross.
“Sheldon Ross’s First Course in Probability reads like a clear, calculus-based undergraduate textbook: definitions, step-by-step derivations, and many worked examples aimed at building formal comfort with probability. What works best is its mathematical clarity — it pushes you through proofs and algebra so you understand why common distributions and counting arguments work. The main limitation is tone and pacing: chapters can feel terse and formula-heavy, and the bundled diskette/tooling feels dated for readers expecting modern software support.”
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Empirical Methods for Artificial Intelligence,
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