Practical Machine Learning in R

Nwanganga, Fred, Chapple, Mike

  • 出版商: Wiley
  • 出版日期: 2020-05-27
  • 定價: $1,500
  • 售價: 9.5$1,425
  • 語言: 英文
  • 頁數: 500
  • 裝訂: Quality Paper - also called trade paper
  • ISBN: 1119591511
  • ISBN-13: 9781119591511
  • 相關分類: Machine Learning
  • 相關翻譯: R語言機器學習實戰 (簡中版)
  • 立即出貨 (庫存=1)




R Programming for Machine Learning shows readers machine learning with a hands on approach to the practical algorithms and applications to solve business problems with machine learning. The book begins by explaining machine learning and its organizational benefits, moves to hands on data management including dimensionality reduction, and then introduces R and the popular RStudio tool. In Unsupervised Learning the reader works with patterns including apriori and eclat and grouping data with clustering (k-means and hierarchical).
From there, R Programming for Machine Learning covers the crucial classification techniques Nearest Neighbor, Decision Trees, and Naive Bayes. The regression techniques are then covered before performance evaluation including choosing the right model and ensemble methods (Random Forest, XGBoost).




FRED NWANGANGA, PHD, is an assistant teaching professor of business analytics at the University of Notre Dame's Mendoza College of Business. He has over 15 years of technology leadership experience.

MIKE CHAPPLE, PHD, is associate teaching professor of information technology, analytics, and operations at the Mendoza College of Business. Mike is a bestselling author of over 25 books, and he currently serves as academic director of the University's Master of Science in Business Analytics program.


FRED NWANGANGA,PHD,是聖母大學門多薩商學院的商業分析助理教授。他擁有超過15年的技術領導經驗。

MIKE CHAPPLE,PHD,是聖母大學門多薩商學院的資訊技術、分析和運營的副教授。Mike是超過25本暢銷書的作者,目前擔任該大學商業分析碩士課程的學術主任。