Machine Learning for Knowledge Discovery with R: Methodologies for Modeling, Inference and Prediction by Kao-Tai Tsai
Requirements: .PDF reader, 12mb
Overview: Machine Learning for Knowledge Discovery with R contains methodologies and examples for statistical modelling, inference, and prediction of data analysis. It includes many recent supervised and unsupervised machine learning methodologies such as recursive partitioning modelling, regularized regression, support vector machine, neural network, clustering, and causal-effect inference. Additionally, it emphasizes statistical thinking of data analysis, use of statistical graphs for data structure exploration, and result presentations. The book includes many real-world data examples from life-science, finance, etc. to illustrate the applications of the methods described therein.
Genre: Non-Fiction > Tech & Devices
Download Instructions:
https://userupload.in/x4qc47x4hcjy
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Requirements: .PDF reader, 12mb
Overview: Machine Learning for Knowledge Discovery with R contains methodologies and examples for statistical modelling, inference, and prediction of data analysis. It includes many recent supervised and unsupervised machine learning methodologies such as recursive partitioning modelling, regularized regression, support vector machine, neural network, clustering, and causal-effect inference. Additionally, it emphasizes statistical thinking of data analysis, use of statistical graphs for data structure exploration, and result presentations. The book includes many real-world data examples from life-science, finance, etc. to illustrate the applications of the methods described therein.
Genre: Non-Fiction > Tech & Devices
Download Instructions:
https://userupload.in/x4qc47x4hcjy
https://dropgalaxy.vip/vlhqjmwnk9w9
Trouble downloading? Read This.