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The Importance of Labeling Data and Combining Large Models with Specific Models
This chapter explores the significance of labeling data and utilizing basic methods to create a model, including unsupervised learning and data labeling for improved performance. The authors recommend scikit-learn and support vector machines as baseline models for faster production, while highlighting the trade-offs of large models and the benefits of combining their strengths with training specific models.