Introduction to Algorithms for Data Mining and Machine Learning

Introduction to Algorithms for Data Mining and Machine Learning introduces the essential ideas behind all key algorithms and techniques for data mining and machine learning, along with optimization techniques. Its strong formal mathematical approach, well selected examples, and practical software recommendations help readers develop confidence in their data modeling skills so they can process and interpret data for classification, clustering, curve-fitting and predictions. Masterfully balancing theory and practice, it is especially useful for those who need relevant, well explained, but not rigorous (proofs based) background theory and clear guidelines for working with big data.

Introduction to Algorithms for Data Mining and Machine Learning features in the following genres: Calculus and mathematical analysis, Applied mathematics

Introduction to Algorithms for Data Mining and Machine Learning is available in Paperback, Ebook

Introduction to Algorithms for Data Mining and Machine Learning was written by XinShe Yang and published by Academic Press an imprint of Elsevier Science

Introduction to Algorithms for Data Mining and Machine Learning has 188 pages