Results for CS103

Mathematical foundations required for computer science, including propositional predicate logic, induction, sets, functions, and relations. Formal language theory, including regular expressions, grammars, finite automata, Turing machines, and NP-completeness. Mathematical rigor, proof techniques, and applications. Prerequisite: 106A or equivalent.

Extracting meaning, information, and structure from human language text, speech, web pages, genome sequences, social networks, or any less structured information. Methods include: string algorithms, edit distance, language modeling, naive Bayes, inverted indices, vector semantics. Applications such as question answering, sentiment analysis, information retrevial, text classification, social network models, machine translation, genomic sequence alignment, spell checking, speech processing. Prerequisite: CS103, CS107, CS109.

Extracting meaning, information, and structure from human language text, speech, web pages, genome sequences, social networks, or any less structured information. Methods include: string algorithms, edit distance, language modeling, naive Bayes, inverted indices, vector semantics. Applications such as question answering, sentiment analysis, information retrevial, text classification, social network models, machine translation, genomic sequence alignment, spell checking, speech processing. Prerequisite: CS103, CS107, CS109.

Extracting meaning, information, and structure from human language text, speech, web pages, genome sequences, social networks, or any less structured information. Methods include: string algorithms, edit distance, language modeling, naive Bayes, inverted indices, vector semantics. Applications such as question answering, sentiment analysis, information retrevial, text classification, social network models, machine translation, genomic sequence alignment, spell checking, speech processing. Prerequisite: CS103, CS107, CS109.