Mining of Massive Datasets van Jure Leskovec, Anand Rajaraman and Jeffrey David Ullman is an English-language textbook intended for higher education and professionals. This book focuses on practical algorithms for data mining and covers applications on very large datasets.
This edition discusses important concepts such as the MapReduce framework for parallel processing, locality-sensitive hashing, and stream processing. It also covers topics including PageRank, frequent itemset mining, clustering, decision trees, deep learning, and the analysis of social network graphs.
This book focuses on practical applications and provides in-depth explanations of algorithms that are essential for students and practitioners in data mining. The content aligns with themes such as data mining, pattern recognition, and artificial intelligence within computer science.