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Statistics with R for Machine Learning: Volume 2 - Mohsen Nady

Statistics with R for Machine Learning: Volume 2

Advanced Resampling Techniques with R for Machine Learning

(Autor)

Buch | Hardcover
185 Seiten
2025
Arcler Press (Verlag)
978-1-77956-471-9 (ISBN)
CHF 249,95 inkl. MwSt
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Unlock advanced resampling techniques to boost model performance in machine learning. Explore cross-validation, bootstrapping, and hyperparameter tuning with R while learning to optimize accuracy and curb overfitting. Engaging examples and case studies illustrate real-world applications for data scientists and enthusiasts.
Resampling techniques are key to improving model performance and reliability in machine learning. This volume explores advanced resampling methods, including cross-validation, bootstrapping, and hyperparameter tuning, using R. Readers will learn how to apply these techniques to optimize model accuracy and prevent overfitting. Practical examples and case studies illustrate their real-world applications. This volume is an essential resource for data scientists and machine learning enthusiasts aiming to master resampling strategies.

Mohsen Nady is a pharmacist with a M.D. in Microbiology and a Diploma in Industrial Pharmacy. Besides, Mohsen has more than 10 years of experience in Statistics and Data Analytics. Mohsen has applied his skills to different projects related to Genomics, Microbiology, Biostatistics, Six Sigma, Data Analytics, Data Visualization, Building Apps, Geography, Market Analysis, Business Analysis, Machine Learning, etc. Mohsen also published his thesis in a high-impact journal that attracted many citations, where all the statistical analyses were performed by him in addition to the methodological part. Furthermore, Mohsen has earned different certificates, from top universities (Harvard, Johns Hopkins, Denmark, etc) in Statistics, Data Analytics, Data Visualization, and Machine Learning that highlight his outstanding diverse skills.

Erscheinungsdatum
Sprache englisch
Maße 152 x 229 mm
Themenwelt Informatik Theorie / Studium Künstliche Intelligenz / Robotik
ISBN-10 1-77956-471-6 / 1779564716
ISBN-13 978-1-77956-471-9 / 9781779564719
Zustand Neuware
Informationen gemäß Produktsicherheitsverordnung (GPSR)
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