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Applied ML
Applied Machine Learning - Welcome
Lecture 1: Introduction to Machine Learning
Lecture 2: Supervised Machine Learning
Lecture 3: Linear Regression
Lecture 4: Classification and Logistic Regression
Lecture 5: Regularization
Lecture 6: Generative Models and Naive Bayes
Lecture 7: Gaussian Discriminant Analysis
Lecture 8: Unsupervised Learning
Lecture 9: Density Estimation
Lecture 10: Clustering
Lecture 12: Support Vector Machines
Lecture 13: Dual Formulation of Support Vector Machines
Lecture 14: Kernels
Lecture 15: Tree-Based Algorithms
Lecture 16: Boosting
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