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Fundamentals of Statistical Modeling and Machine Learning Techniques
Statistical Terminology and Machine Learning
The Course Overview (2:21)
Machine Learning (5:27)
Statistical Terminology for Model Building and Validation (19:46)
Bias Versus Variance Trade-Off (3:59)
Machine Learning Terminology for Model Building and Validation
Linear Regression Versus Gradient Descent (4:47)
Machine Learning Losses (1:51)
Train, Validation, and Test Data (2:07)
Cross-Validation and Grid Search (4:02)
Machine Learning Model Overview (5:31)
Linear Regression
Compensating Factors in Machine Learning Models (7:24)
Simple Linear Regression from First Principles (3:49)
Simple Linear Regression Using Wine Quality Data (2:58)
Multi-Linear Regression (7:28)
Linear Regression Model – Ridge Regression (3:59)
Linear Regression Model – Lasso Regression (3:07)
Logistic Regression Versus Random Forest
Maximum Likelihood Estimation (3:37)
Logistic Regression (25:13)
Random Forest (8:11)
Variable Importance Plot (4:38)
Compensating Factors in Machine Learning Models
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