• Chapter 3: Classification

    Welcome to an Exciting Chapter on Pycaret!

    In this Chapter your will learn about Datasets, Data Preparation (Setup), Model Training & Selection, Build the model using Best MODEL, Analyze the best model, predict new Data, Check feature importance, Dashboard, Hyperparameter tuning, Interpret the results AUC Plot Precision-Recall Curve Confusion Matrix, Cross-validation, Finalize and Save Pipeline

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        Learning Objective 

        Classification (Notes)(Code)

        • Datasets
        • Data Preparation (Setup)
        • Model Training & Selection
        • Build the model using Best MODEL
        • Analyze the best model
        • Predict new Data
        • Check feature importance
        • Dashboard
        • Hyperparameter tuning
        • Interpret the results
        • AUC Plot
        • Precision-Recall Curve
        • Confusion Matrix
        • Cross-validation
        • Finalize and Save Pipeline