{"product_id":"applied-machine-learning-using-mlr3-in-r-9781032507545","title":"Applied Machine Learning Using mlr3 in R","description":"\u003cb\u003eBook Synopsis\u003c\/b\u003e\u003cbr\u003e\u003cp\u003emlr3 is an award-winning ecosystem of R packages that have been developed to enable state-of-the-art machine learning capabilities in R. \u003cb\u003eApplied Machine Learning Using mlr3 in R\u003c\/b\u003e gives an overview of flexible and robust machine learning methods, with an emphasis on how to implement them using mlr3 in R. It covers various key topics, including basic machine learning tasks, such as building and evaluating a predictive model; hyperparameter tuning of machine learning approaches to obtain peak performance; building machine learning pipelines that perform complex operations such as pre-processing followed by modelling followed by aggregation of predictions; and extending the mlr3 ecosystem with custom learners, measures, or pipeline components.\u003c\/p\u003e\u003cp\u003eFeatures:\u003c\/p\u003e\u003cul\u003e\n\u003cli\u003eIn-depth coverage of the mlr3 ecosystem for users and developers\u003c\/li\u003e\n\u003cli\u003eExplanation and illustration of basic and advanced machine learning concepts\u003c\/li\u003e\n\u003cli\u003eReady to use code samples that can be adapted by the use\u003cbr\u003e\u003cbr\u003e\u003cb\u003eTable of Contents\u003c\/b\u003e\u003cbr\u003e\u003cp\u003e1. \u003cb\u003eIntroduction and Overview\u003c\/b\u003e. 2. \u003cb\u003eData and Basic Modeling\u003c\/b\u003e. 3. \u003cb\u003eEvaluation and Benchmarking\u003c\/b\u003e. 4. \u003cb\u003eHyperparameter Optimization\u003c\/b\u003e. 5. \u003cb\u003eAdvanced Tuning Methods and Black Box Optimization\u003c\/b\u003e. 6. \u003cb\u003eFeature Selection\u003c\/b\u003e. 7. \u003cb\u003eSequential Pipelines\u003c\/b\u003e. 8. \u003cb\u003eNon-sequential Pipelines and Tuning\u003c\/b\u003e. 9. \u003cb\u003ePreprocessing. \u003c\/b\u003e10. \u003cb\u003eAdvanced Technical Aspects of mlr3 \u003c\/b\u003e.11. \u003cb\u003eModel Interpretation and Explanation. \u003c\/b\u003e12.\u003cb\u003e Model Interpretatio\u003c\/b\u003en. 13. \u003cb\u003eBeyond Regression and Classification. \u003c\/b\u003e14.\u003cb\u003e Algorithmic Fairness.\u003c\/b\u003e\u003c\/p\u003e\n\u003c\/li\u003e\n\u003c\/ul\u003e","brand":"Taylor \u0026 Francis Ltd","offers":[{"title":"Default Title","offer_id":51019094163799,"sku":"9781032507545","price":58.89,"currency_code":"GBP","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0817\/1739\/5799\/files\/9781032507545.jpg?v=1750779283","url":"https:\/\/bookcurl.com\/products\/applied-machine-learning-using-mlr3-in-r-9781032507545","provider":"Book Curl","version":"1.0","type":"link"}