Introduction
Speed meets strategy: Why pretrained models change everything
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From scratch to pretrained: Understanding the shift and staying critical
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Quick start: A look at our final model
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1. Model Selection
Navigating Hugging Face's model portfolio
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Problem set introduction
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Selecting a relevant model
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Preparing your development environment
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2. Effective Feature Engineering
Crafting a relevant dataset
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Exploratory data analysis
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Setting model parameters
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Preprocessing assumptions
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Run model
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3. Model Evaluation
Defining success metrics
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Out-of-the-box metrics
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Hugging Face Evaluate library
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Going deeper: Results by class
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Calibration thresholds
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Going deeper: Misclassification analysis
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Feature importance plots
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Try it again: Running the next iteration
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Conclusion
Finalize model for production
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Conclusion
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