Fundamentals of Data Mining PDF Notes, Books Course Data and Tutorials
Introduction to Fundamentals of Data Mining
Data mining is the method of finding models in large data assortments including methods at the intersection of machine learning, statistics, and database systems. Data mining is an imporant subfield of computer science with an overall purpose to obtain information (with the intelligent scheme) from a data set and change the information into a coherent structure for additional use. Data mining is the analysis level of the “knowledge results in databases“ process or KDD. Apart from the immature analysis level, it also includes database and data management features, data pre-processing, model and outcome considerations, interestingness metrics, complexity insights, post-processing of observed edifices, 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 by Jiawei Han, Micheline Kamber, Jian Pei
- Data Mining: Concepts, Models, Methods, and Algorithms by Mehmed Kantatardzic
- Data Mining, Introductory and Advanced Topics by Margaret H. Dunham and S. Sridhar
- Principles of Data Miningby 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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