(Weeks 9–10 | Lec 6 Hrs / Lab 18 Hrs / Ext 0 Hrs | 24 Total Hrs | 1.0 Credit Hrs)
Students will:
Use scikit-learn pipelines for ML workflows
Prerequisite: DSEng 104 – Data Visualization & Storytelling
Tools: Scikit-learn, Pandas, Matplotlib
Build supervised learning models (regression, classification)
Implement model evaluation metrics (precision, recall, F1-score)
Perform feature engineering and model selection
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