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A Hands-On Introduction to Data Science-CUP (2020).pdf
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This book introduces the field of data science in a practical and accessible manner, using a hands-on approach that assumes no prior knowledge of the subject. The foundational ideas and techniques of data science are provided independently from technology, allowing students to easily develop a firm understanding of the subject without a strong technical background, as well as being presented with material that will have continual relevance even after tools and technologies change. Using popular data science tools such as Python and R, the book offers many examples of real-life applications, with practice ranging from small to big data. A suite of online material for both instructors and students provides a strong supplement to the book, including datasets, chapter slides, solutions, sample exams and curriculum suggestions. This entry-level textbook is ideally suited to readers from a range of disciplines wishing to build a practical, working knowledge of data science.
Table of contents :
1 Introduction
2 Data
3 Techniques
4 UNIX
5 Python
6 R
7 MySQL
8 Machine Learning Introduction and Regression
9 Supervised Learning
10 Unsupervised Learning
11 Hands-On with Solving Data Problems
12 Data Collection, Experimentation, and Evaluation
Appendix A:Useful Formulas from Differential Calculus
Appendix B:Useful Formulas from Probability
Appendix C:Useful Resources
Appendix D:Installing and Configuring Tools
Appendix E:Datasets and Data Challenges
Appendix F:Using Cloud Services
Appendix G:Data Science Jobs
Appendix H:Data Science and Ethics
Appendix I:Data Science for Social Good
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