Learning Data Science

Frontmatter

To the Data 100 Student
Prerequisites
Notation

The Data Science Lifecycle

1. The Data Science Lifecycle
2. Questions and Data Scope
3. Simulation and Data Design
4. Modeling with Summary Statistics
5. Case Study: Why is my Bus Always Late?

Rectangular Data

6. Working With Dataframes Using pandas
7. Working With Relations Using SQL

Understanding The Data

8. Wrangling Files
9. Wrangling Dataframes
10. Exploratory Data Analysis
11. Data Visualization
12. Case Study: How Accurate are Air Quality Measurements?

Other Data Sources

13. Working with Text
14. Web Technologies

Linear Modeling

15. Linear Models
16. Model Selection
17. Theory for Inference and Prediction
18. Case Study: How to Weigh a Donkey

Classification

19. Classification
20. Numerical Optimization
21. Case Study: Detecting Fake News

Appendices

Probability Review
Vector Space Review
Statistical Inference Review
- Hypothesis Testing and Confidence Intervals
- Permutation Test
Reference Tables
The Bias-Variance Tradeoff
Regularization
Replicable Research
- P-hacking
Dimensionality Reduction and PCA
Decision Trees and Random Forests
Clustering
Contributors
References

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Modeling

21.4. Modeling¶

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21.3. Exploring the Data

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21.5. Summary

By Sam Lau, Joey Gonzalez, and Deb Nolan
© Copyright 2023.

License: CC BY-NC-ND 4.0