"Data Mining: Methods, Applications and Systems" ed. by Derya Birant

This book presents recent theoretical and practical advances in the field of data mining. It discusses a number of data mining methods, including classification, clustering, and association rule mining.


Data mining is a branch of computer science that is used to automatically extract meaningful, useful knowledge and previously unknown, hidden, interesting patterns from a large amount of data to support the decision-making process.
This book brings together many different successful data mining studies in various areas such as health, banking, education, software engineering, animal science, and the environment.


Contents
1. Deep Learning: Exemplar Studies in Natural Language Processing and Computer Vision
2. Contribution to Decision Tree Induction with Python: A Review
3. Association Rule Mining on Big Data Sets
4. Data Mining in Banking Sector Using Weighted Decision Jungle Method
5. Analytical Statistics Techniques of Classification and Regression in Machine Learning
6. Clustering of Time-Series Data
7. Weather Nowcasting Using Deep Learning Techniques
8. Data Mining and Machine Learning for Software Engineering
9. Data Mining for Student Performance Prediction in Education
10. Tracer Transport in a Homogeneous Porous Medium: Experimental Study and Acquisition Data with LabVIEW
11. Data Mining and Fuzzy Data Mining Using MapReduce Algorithms


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