Supervised Machine Learning | Optimization Framework and Applications with SAS and R
Tanya Kolosova (u. a.)
ISBN 10: 0367277328 ISBN 13: 9780367277321
Editorial: Chapman and Hall/CRC, 2020
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preigu, Osnabrück, Alemania
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Descripción
Descripción:
Supervised Machine Learning | Optimization Framework and Applications with SAS and R | Tanya Kolosova (u. a.) | Buch | Einband - fest (Hardcover) | Englisch | 2020 | Chapman and Hall/CRC | EAN 9780367277321 | Verantwortliche Person für die EU: Libri GmbH, Europaallee 1, 36244 Bad Hersfeld, gpsr[at]libri[dot]de | Anbieter: preigu Print on Demand. N° de ref. del artículo 131402254
Sinopsis:
AI framework intended to solve a problem of bias-variance tradeoff for supervised learning methods in real-life applications. It comprises of bootstrapping to create multiple training and testing data sets, design and analysis of statistical experiments and optimal hyper-parameters for ML methods.
Acerca del autor:
Tanya Kolosova is a statistician, software engineer, an educator, and a co-author of two books on statistical analysis and metadata-based applications development using SAS. Tanya is an actionable analytics expert, she has extensive knowledge of software development methods and technologies, artificial intelligence methods and algorithms, and statistically designed experiments.
Samuel Berestizhevsky is a statistician, researcher and software engineer. Together with Tanya, Samuel co-authored two books on statistical analysis and metadata-based applications development using SAS. Samuel is an innovator and an expert in the area of automated actionable analytics and artificial intelligence solutions. His extensive knowledge of software development methods, technologies and algorithms allows him to develop solutions on the cutting edge of science.
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Detalles bibliográficos
Título: Supervised Machine Learning | Optimization ...
Editorial: Chapman and Hall/CRC
Año de publicación: 2020
Encuadernación: Buch
Condición: Neu