ISBN-13: 9781108958509 / Angielski / Miękka / 2022 / 75 str.
A practical guide to text classification and neural networks in Python for social scientists.
1. Introduction; 2. Ethics, Fairness, and Bias; 3. Classification; 4. Text as Input; 5. Labels; 6. Train-Dev-Test; 7. Performance Metrics; 8. Comparison and Significance Testing; 9. Overfitting and Regularization; 10. Model Selection and Other Classifiers; 11. Model Bias; 12. Feature Selection; 13. Structured Prediction; 14. Neural Networks Background; 15. Neural Architectures and Models.
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