Textbook in PDF format

The book systematically introduces the basic contents of data science, including data preprocessing and basic methods of data analysis, handling special problems (e.g. text analysis), deep learning, and distributed systems. In addition to systematically introducing the basic content of data science from a theoretical point of view, the book also provides a large number of data analysis practice cases.
Preface.
About the Authors.
About the Translators.
Introduction.
Data Preprocessing.
Regression Model.
Classification Model.
Ensemble Method.
Clustering Model.
Association Rule Mining.
Dimensionality Reduction.
Feature Selection.
EM Algorithm.
Probabilistic Graphical Model.
Text Analysis.
Graph and Network Analysis.
Deep Learning.
Distributed Computing.
Appendix A Matrix Operation.
Appendix B Probability Basis.
Appendix C Optimization Algorithm.
Appendix D Distance.
Appendix E Model Evaluation.
References