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Course Content
Course Overview
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Unit 1 – Defining the Problem & Selecting Baseline Models
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Unit 2 – Model Training & Cross-Validation
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Unit 3 – Hyperparameter Tuning GridSearch, Random & Bayesian
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Unit 4 – Multi-Model Comparison
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Unit 5 – Predicting & Evaluation Metrics
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Unit 6 – Visualizing Model Performance
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Unit 7 – Cross-Validation & Final Model Selection
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Unit 8 – Model Interpretation & Explainability
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