2019’s Best Fundamentals of Data Mining pdf Notes, Books Course Data and Tutorials
Introduction to Fundamentals of Data Mining
Data mining is the process of discovering patterns in large data sets involving methods at the intersection of machine learning, statistics, and database systems. Data mining is an interdisciplinary subfield of computer science with an overall goal to extract information (with the intelligent method) from a data set and transform the information into a comprehensible structure for further use. Data mining is the analysis step of the “knowledge discovery in databases“ process or KDD. Aside from the raw analysis step, it also involves database and data management aspects, data pre-processing, model and inference considerations, interestingness metrics, complexity considerations, post-processing of discovered structures, visualization, and online updating.
This Outline Will be similar with your University Course Outline for Fundamentals of Data Mining Course.
Concepts of Data mining, data pre-processing and pre-mining,(noisy and missing data, data normalization and discretization), outlier detection, Data mining learning methods, Data mining classes (association rule mining, clustering, classification), fundamental of other algorithms related to data mining(fuzzy logic, genetic algorithm and neural network), decision trees, rules, patterns and trends
Best Recommended Fundamentals of Data Mining PDF Notes and Books in Universities:
Here is detailed list of best Fundamentals of Data Mining books for Universities:
- Data Mining: Concepts and Techniques, 3rd Edition Jiawei Han, Micheline Kamber, Jian Pei; , 2011
- Data Mining: Concepts, Models, Methods, and Algorithms, 2nd Edition, Mehmed Kantatardzic, 2011.
- Data Mining, Introductory and Advanced Topics, 2006, Margaret H. Dunham and S. Sridhar, PearsonEducation.
- Principles of Data Mining, 2007, Max Bramer, Springer-Verlag
Fundamentals of Data Mining Video Tutorials
Introduction to Data Mining by Data Science Dojo
Fundamentals of Data Mining by Binh Nguyen
Data Mining by Stan Forrester
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