Day141 - STAT Review: Statistical Machine Learning (3)
Practical Statistics for Data Scientists: K-Nearest Neighbors (3) (KNN as a Feature Engine) & Tree Models (1) (Key Concepts)
Recent posts
Day140 - STAT Review: Statistical Machine Learning (2)
Practical Statistics for Data Scientists: K-Nearest Neighbors (2) (Standardization & Choosing K)
Day139 - STAT Review: Statistical Machine Learning (1)
Practical Statistics for Data Scientists: K-Nearest Neighbors (1) (Example, Distance Metrics, and One Hot Encoder)
Day138 - STAT Review: Classification (8)
Practical Statistics for Data Scientists: Strategies for Imbalanced Data (2) (Data Generation, Cost-Based Classification, and Exploring the Predictions)
Day137 - STAT Review: Classification (7)
Practical Statistics for Data Scientists: Strategies for Imbalanced Data (1) (Undersampling & Oversampling)
Day136 - STAT Review: Classification (6)
Practical Statistics for Data Scientists: Evaluating Classification Models (Confusion Matrix, ROC-AUC & Lift)
Day135 - STAT Review: Classification (5)
Practical Statistics for Data Scientists: Logistic Regression (3) Assessing the Model
Day134 - STAT Review: Classification (4)
Practical Statistics for Data Scientists: Logistic Regression (2) (GLM, Interpretation, Fitting the Model)
Day133 - STAT Review: Classification (3)
Practical Statistics for Data Scientists: Logistic Regression (1) (Mathematical Foundation: Odds, Logit Function, Formula, and Examples)
Day132 - STAT Review: Classification (2)
Practical Statistics for Data Scientists: Discriminant Analysis (Covariance, Discriminant Function, and Application: Predicting Default Risk)