'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.

“数据挖掘和机器学习算法简介”介绍了数据挖掘和机器学习的所有关键算法和技术背后的基本思想，以及优化技术。其强大的形式化数学方法、精心挑选的示例和实用的软件建议有助于读者建立对其数据建模技能的信心，以便他们能够处理和解释分类、聚类、曲线拟合和预测所需的数据。它巧妙地平衡了理论和实践，对于那些需要相关的、解释良好但不严格（基于证据的）背景理论和清晰的大数据工作指南的人来说尤其有用。