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  • with Applications in R
    Gareth James; Daniela Witten; Trevor Hastie; Robert Tibshirani
    978-1-0716-1418-1
    2021
    Edition 2
    • Presents an essential statistical learning toolkit for practitioners in science, industry, and other fields
    • Demonstrates application of the statistical learning methods in R
    • Includes new chapters on deep learning, survival analysis, and multiple testing
    • Covers a range of topics, such as linear regression, classification, resampling methods, shrinkage approaches, tree-based methods, support vector machines, clustering, and deep learning
    • Features extensive color graphics for a dynamic learning experience
    • Includes supplementary material: sn.pub/extras

    €419

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