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Applied linguistics --- Linguistique appliquée --- Periodicals. --- Périodiques --- Arts and Humanities --- Language & Linguistics --- applied linguistics --- mother tongue --- second-language teaching --- first and second language acquisition --- Applied linguistics. --- Linguistics --- language teaching --- language acquisition --- language learning --- language policy and planning

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Sociolinguistics --- Bilingualism --- Language acquisition --- Bilinguisme --- Langage --- Periodicals. --- Périodiques --- Acquisition --- Tweetaligheid. --- Arts and Humanities --- Social Sciences --- General and Others --- Language & Linguistics --- Behavioral Science (Psychology) and Counselling --- Bilingualism. --- Language acquisition. --- Acquisition of language --- Developmental linguistics --- Developmental psycholinguistics --- Language and languages --- Language development in children --- Psycholinguistics, Developmental --- Interpersonal communication in children --- Psycholinguistics --- Languages in contact --- Multilingualism

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The fundamental mathematical tools needed to understand machine learning include linear algebra, analytic geometry, matrix decompositions, vector calculus, optimization, probability and statistics. These topics are traditionally taught in disparate courses, making it hard for data science or computer science students, or professionals, to efficiently learn the mathematics. This self-contained textbook bridges the gap between mathematical and machine learning texts, introducing the mathematical concepts with a minimum of prerequisites. It uses these concepts to derive four central machine learning methods: linear regression, principal component analysis, Gaussian mixture models and support vector machines. For students and others with a mathematical background, these derivations provide a starting point to machine learning texts. For those learning the mathematics for the first time, the methods help build intuition and practical experience with applying mathematical concepts. Every chapter includes worked examples and exercises to test understanding. Programming tutorials are offered on the book's web site. (4ème de couverture)

Machine learning --- Mathematics --- Learning, Machine --- Artificial intelligence --- Machine theory --- 681.3*I26 --- 681.3*I26 Learning: analogies; concept learning; induction; knowledge acquisition; language acquisition; parameter learning (Artificial intelligence)--See also {681.3*K32} --- Learning: analogies; concept learning; induction; knowledge acquisition; language acquisition; parameter learning (Artificial intelligence)--See also {681.3*K32} --- toegepaste wiskunde --- Apprentissage automatique. --- Mathématiques. --- Machine learning. --- Mathematics. --- Apprentissage automatique --- Mathématiques --- Mathématiques. --- Machine learning - Mathematics --- Mathématiques

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Didactics of languages --- Language and languages --- Business --- Study and teaching (Higher) --- Language --- Arts and Humanities --- Language & Linguistics --- Trade --- Foreign languages --- Languages --- Economics --- Management --- Commerce --- Industrial management --- Anthropology --- Communication --- Ethnology --- Information theory --- Meaning (Psychology) --- Philology --- Linguistics --- applied linguistics --- business language --- professional communication --- second language acquisition --- language teaching --- language for specific purposes