- EDA For Classification Pro
- Defining a Target Pro
- DEMO: Defining a Target Pro
- Exploring the Target Pro
- Exploring the Features Pro
- DEMO: Exploring the Features Pro
- ASSIGNMENT: Exploring the Target & Features Pro
- SOLUTION: Exploring the Target & Features Pro
- Correlation Pro
- PRO TIP: Correlation Matrix Pro
- DEMO: Correlation Matrix Pro
- Feature-Target Relationships Pro
- Feature-Feature Relationships Pro
- PRO TIP: Pair Plots Pro
- ASSIGNMENT: Exploring Relationships Pro
- SOLUTION: Exploring Relationships Pro
- Feature Engineering Overview Pro
- Numeric Feature Engineering Pro
- Dummy Variables Pro
- Binning Categories Pro
- DEMO: Feature Engineering Pro
- Data Splitting Pro
- Preparing Data For Modeling Pro
- ASSIGNMENT: Preparing the Data for Modeling Pro
- SOLUTION: Preparing the Data for Modeling Pro
- Key Takeaways Pro
- QUIZ: Data Prep & EDA Pro
- K-Nearest Neighbors Pro
- The KNN Workflow Pro
- KNN in Python Pro
- Model Accuracy Pro
- Confusion Matrix Pro
- DEMO: Confusion Matrix Pro
- ASSIGNMENT: Fitting A Simple KNN Model Pro
- SOLUTION: Fitting A Simple KNN Model Pro
- Hyperparameter Tuning Pro
- Overfitting & Validation Pro
- DEMO: Hyperparameter Tuning Pro
- Hard vs. Soft Classification Pro
- DEMO: Probability vs. Event Rate Pro
- ASSIGNMENT: Tuning a KNN Model Pro
- SOLUTION: Tuning a KNN Model Pro
- Pros & Cons of KNN Pro
- Key Takeaways Pro
- QUIZ: K-Nearest Neighbors Pro
- Logistic Regression Pro
- Logistic vs. Linear Regression Pro
- The Logistic Function Pro
- Likelihood Pro
- Multiple Logistic Regression Pro
- The Logistic Regression Workflow Pro
- Logistic Regression in Python Pro
- Interpreting Coefficients Pro
- ASSIGNMENT: Logistic Regression Pro
- SOLUTION: Logistic Regression Pro
- Feature Engineering & Selection Pro
- Regularization Pro
- Tuning a Regularized Model Pro
- ASSIGNMENT: Regularized Logistic Regression Pro
- SOLUTION: Regularized Logistic Regression Pro
- Multi-class Logistic Regression Pro
- ASSIGNMENT: Multi-class Logistic Regression Pro
- SOLUTION: Multi-class Logistic Regression Pro
- Pros & Cons of Logistic Regression Pro
- Key Takeaways Pro
- QUIZ: Logistic Regression Pro
- Classification Metrics Pro
- Accuracy, Precision & Recall Pro
- DEMO: Accuracy, Precision & Recall Pro
- PRO TIP: F1 Score Pro
- ASSIGNMENT: Model Metrics Pro
- SOLUTION: Model Metrics Pro
- Soft Classification Pro
- DEMO: Leveraging Soft Classification Pro
- PRO TIP: Precision-Recall & F1 Curves Pro
- DEMO: Plotting Precision-Recall & F1 Curves Pro
- The ROC Curve & AUC Pro
- DEMO: The ROC Curve & AUC Pro
- Classification Metrics Recap Pro
- ASSIGNMENT: Threshold Shifting Pro
- SOLUTION: Threshold Shifting Pro
- Multi-class Metrics Pro
- Multi-class Metrics in Python Pro
- ASSIGNMENT: Multi-class Metrics Pro
- SOLUTION: Multi-class Metrics Pro
- Key Takeaways Pro
- QUIZ: Classification Metrics Pro
- Imbalanced Data Pro
- Managing Imbalanced Data Pro
- Threshold Shifting Pro
- Sampling Strategies Pro
- Oversampling Pro
- Oversampling in Python Pro
- DEMO: Oversampling Pro
- SMOTE Pro
- SMOTE in Python Pro
- Undersampling Pro
- Undersampling in Python Pro
- ASSIGNMENT: Sampling Methods Pro
- SOLUTION: Sampling Methods Pro
- Changing Class Weights Pro
- DEMO: Changing Class Weights Pro
- ASSIGNMENT: Changing Class Weights Pro
- SOLUTION: Changing Class Weights Pro
- Imbalanced Data Recap Pro
- Key Takeaways Pro
- QUIZ: Imbalanced Data Pro
- Decision Trees Pro
- Entropy Pro
- Decision Tree Predictions Pro
- Decision Trees in Python Pro
- DEMO: Decision Trees Pro
- Feature Importance Pro
- ASSIGNMENT: Decision Trees Pro
- SOLUTION: Decision Trees Pro
- Hyperparameter Tuning for Decision Trees Pro
- DEMO: Hyperparameter Tuning Pro
- ASSIGNMENT: Tuned Decision Tree Pro
- SOLUTION: Tuned Decision Tree Pro
- Pros & Cons of Decision Trees Pro
- Key Takeaways Pro
- QUIZ: Decision Trees Pro
- Ensemble Models Pro
- Simple Ensemble Models Pro
- DEMO: Simple Ensemble Models Pro
- ASSIGNMENT: Simple Ensemble Models Pro
- SOLUTION: Simple Ensemble Models Pro
- Random Forests Pro
- Fitting Random Forests in Python Pro
- Hyperparameter Tuning for Random Forests Pro
- PRO TIP: Random Search Pro
- Pros & Cons of Random Forests Pro
- ASSIGNMENT: Random Forests Pro
- SOLUTION: Random Forests Pro
- Gradient Boosting Pro
- Gradient Boosting in Python Pro
- Hyperparameter Tuning for Gradient Boosting Pro
- DEMO: Hyperparameter Tuning for Gradient Boosting Pro
- Pros & Cons of Gradient Boosting Pro
- ASSIGNMENT: Gradient Boosting Pro
- SOLUTION: Gradient Boosting Pro
- PRO TIP: SHAP Values Pro
- DEMO: SHAP Values Pro
- Key Takeaways Pro
- QUIZ: Ensemble Models Pro