Data science bookcamp: five Python projects

"A data science project has a lot of moving parts, and it takes practice and skill to get all the code, algorithms, datasets, formats, and visualizations working together harmoniously. This unique book guides you through five realistic projects, including tracking disease outbreaks from news headlines, analyzing social networks, and finding relevant patterns in ad click data. "Data science bookcamp" doesn't stop with surface-level theory and toy examples. As you work through each project, you'll learn how to troubleshoot common problems like missing data, messy data, and algorithms that don't quite fit the model you're building. You'll appreciate the detailed setup instructions and the fully explained solutions that highlight common failure points. In the end, you'll be confident in your skills because you can see the results."--Back cover.

Subtitle on cover: five real-world Python projects.

1. Computing probabilities using Python -- 2. Plotting probabilities using Matplotlib -- 3. Running random simulations in NumPy -- 4. Case study 1 solution -- 5. Basic probability and statistical analysis using SciPy -- 6. Making predictions using the central limit theorem and SciPy -- 7. Statistical hypothesis testing -- 8. Analyzing tables using Pandas -- 9. Case study 2 solution -- 10. Clustering data into groups -- 11. Geographic location visualization and analysis -- 12. Case study 3 solution -- 13. Measuring text similarities -- 14. Dimension reduction of matrix data -- 15. NLP analysis of large text datasets -- 16. Extracting text from web pages -- 17. Case study 4 solution -- 18. An introduction to graph theory and network analysis -- 19. Dynamic graph theory techniques for node ranking and social network analysis -- 20. Network-driven supervised machine learning -- 21. Training linear classifiers with logistic regression -- 22. Training nonlinear classifiers with decision tree techniques -- 23. Case study 5 solution.