Machine Learning course taught by Dr. Mohamed-Rafik Bouguelia, at Halmstad University, Sweden. This part of the classification lecture presents the k-Nearest-Neighbors classifier (kNN).
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Lecture 1 (Part 1) Introduction - Machine Learning Course
Lecture 1 (Part 2) - Basics of Machine Learning and Prerequisites - Machine Learning Course
Lecture 2 (Part 1) - Linear Regression - Machine Learning Course
Lecture 2 (Part 2) - Nonlinear Regression (with Kernels, kNN, Features) - Machine Learning Course
Lecture 2 (Part 3) - Questions and Answers (Quiz) - Machine Learning Course
Lecture 3 (Part 1) - Linear Classification with Logistic Regression - Machine Learning Course
Lecture 3 (Part 2) - Logistic Regression with Nonlinear Features - Machine Learning Course
Lecture 3 (Part 3) - k Nearest Neighbors Classifier kNN - Machine Learning Course
Lecture 4 (Part 1) - Decision Tree and Random Forest and Regression Tree - Machine Learning Course
Lecture 4 (Part 2) - Questions and Answers (Quiz) - Machine Learning Course
Lecture 5 - Overfitting, underfitting, Generalization and Regularization - Machine Learning Course
Lecture 6 (Part 1) - Support Vector Machine (SVM) and Kernel Trick - Machine Learning Course