Read “Data Mining: Concepts and Techniques” by Jiawei Han with Rakuten Data Mining: Concepts and Techniques ebook by Jiawei Han,Micheline Kamber . Data Mining: Concepts and Techniques (The Morgan Kaufmann Series in Data Management Systems) [Jiawei Han, Micheline Kamber, Jian Pei] on. Editorial Reviews. Review. The increasing volume of data in modern business and Techniques (The Morgan Kaufmann Series in Data Management Systems) eBook: Jiawei Han, Jian Pei, Micheline Kamber: Kindle Store.
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See if you have enough points for this item. Concepts and Techniques provides the concepts and techniques in processing gathered data or information, which will be used in various applications. Specifically, it explains data mining and the tools used in discovering knowledge from the collected data.
This book is referred as the knowledge discovery from data KDD. It focuses on sata feasibility, usefulness, effectiveness, and scalability of techniques of large data sets. After describing data mining, this edition explains the methods of knowing, preprocessing, processing, and warehousing data.
It then presents information about egook warehouses, online analytical processing OLAPand data cube technology. Then, the methods involved in mining frequent patterns, associations, and correlations for large data sets are described. The book details the methods for data classification and introduces the concepts and methods for data clustering.
The remaining chapters discuss the outlier detection and kambrr trends, applications, and research frontiers in data mining. This book is intended for Computer Science students, application developers, business professionals, and researchers who seek information on data mining.
Introduction to Information Retrieval. TensorFlow for Deep Learning. Machine Learning and Security. Mastering Java Machine Learning. Machine Learning for Data Kmber. Handbook of Big Data Technologies. Deep Learning with Hadoop. A General Introduction to Data Analytics. Database Systems for Advanced Applications. Data Mining and Constraint Programming.
Advances in Knowledge Discovery and Data Mining. Machine Learning for Text. Clustering and Information Retrieval. Web and Big Data. Formal Aspects of Component Software. Principles and Practice of Constraint Programming. Applied Cryptography and Network Security.
Data Mining: Concepts and Techniques,
Software Engineering and Methodology for Emerging Domains. Measurement, Modelling and Evaluation of Computing Systems. Advances in Artificial Intelligence. Information and Communications Security.
Algorithmic Aspects of Cloud Computing. Mastering Predictive Analytics with Python. Big Data Analytics and Knowledge Discovery. Differential Privacy and Applications. Analytic Methods daya Systems and Software Testing. Pro Power BI Desktop. Risks and Security of Internet and Systems. SQL in a Nutshell. Workload Characterization for Computer System Design.
Data Mining: Concepts and Techniques – Jiawei Han – Google Books
Field Guide to Hadoop. Fundamental Approaches to Software Engineering. Data Mining Applications with R. Mastering Data Analysis with R. Data Science and Big Data: An Environment of Computational Intelligence. Tools and Algorithms for the Construction and Analysis ka,ber Systems.
Lectures on Runtime Verification. An Introduction to Description Logic. Advanced Backend Code Optimization.
Handbook of Constraint Programming. Miining Management and Acquisition for Intelligent Systems. Data Science with Java.
Information Reuse and Integration in Academia and Industry. Databases Theory and Applications. Foundations and Practice of Security.
Advances bh K-means Clustering. Mining Heterogeneous Information Networks. Models, Algorithms, and Applications. How to write a great review. The review must be at least 50 characters long. The title should be at least 4 characters long. Your display name should be at least 2 characters long.
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Please review your cart. You can remove the unavailable item s now or we’ll automatically remove it at Checkout. Continue shopping Checkout Continue shopping. Chi ama i libri sceglie Kobo e inMondadori. Home eBooks Nonfiction Data Mining: Concepts and Techniques Back to Nonfiction. Or, get it for Kobo Super Points! Presents dozens of algorithms and implementation examples, all in pseudo-code and suitable for use in real-world, large-scale data mining projects Addresses advanced topics such as mining object-relational databases, spatial databases, multimedia databases, time-series databases, text databases, the World Wide Web, and applications in several fields Provides a comprehensive, practical look at the concepts and techniques you need to get the most out of your data.
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