Machine Learning for Hackers [ Livre] / Drew, Conway / John Myles, White

Auteur principal: Conway, DrewCo-auteur: White, John MylesLangue: Anglais ; de l'oeuvre originale, Anglais.Publication : Sebastopol : Oreilly Medi Inc, 2012Description : 1 vol (XIIII-303 p.) ; 24 cmISBN: 9781449303716.Classification: I Intelligence artificielle, Machine Learning et Data ScienceRésumé: If you're an experienced programmer interested in crunching data, this book will get you started with machine learning a toolkit of algorithms that enables computers to train themselves to automate useful tasks. Authors Drew Conway and John Myles White help you understand machine learning and statistics tools through a series of hands-on case studies, instead of a traditional math-heavy presentation. Each chapter focuses on a specific problem in machine learning, such as classification, prediction, optimization, and recommendation. Using the R programming language, you'll learn how to analyze sample datasets and write simple machine learning algorithms. Machine Learning for Hackers is ideal for programmers from any background, including business, government, and academic research..Sujet - Nom commun: Apprentissage automatique
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I CON (Browse shelf) Checked out I Intelligence artificielle, Machine Learning et Data Science 29/11/2021 041371

If you're an experienced programmer interested in crunching data, this book will get you started with machine learning a toolkit of algorithms that enables computers to train themselves to automate useful tasks. Authors Drew Conway and John Myles White help you understand machine learning and statistics tools through a series of hands-on case studies, instead of a traditional math-heavy presentation. Each chapter focuses on a specific problem in machine learning, such as classification, prediction, optimization, and recommendation. Using the R programming language, you'll learn how to analyze sample datasets and write simple machine learning algorithms. Machine Learning for Hackers is ideal for programmers from any background, including business, government, and academic research.

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