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Data Science: A First Introduction with Python

Front Matter

Preface
Foreword
Acknowledgments
About the authors

Chapters

1. Python and Pandas
2. Reading in data locally and from the web
3. Cleaning and wrangling data
4. Effective data visualization
5. Classification I: training & predicting
6. Classification II: evaluation & tuning
7. Regression I: K-nearest neighbors
8. Regression II: linear regression
9. Clustering
10. Statistical inference
11. Combining code and text with Jupyter
12. Collaboration with version control
13. Setting up your computer

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By Tiffany Timbers, Trevor Campbell, Melissa Lee, Joel Ostblom, and Lindsey Heagy

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