| Introduction to the Class |
 Introduction |
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 Recorded Lecture 20/21: Introduction and kNN |
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Python and NumPy Primer |
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Python Cheatsheet |
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Matplotlib Cheatsheet |
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Recorded Lecture 20/21: Python and NumPy Primer |
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 Exercise 1: Introduction to Python |
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 Exercise 1: Introduction to Python Solutions |
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Exercise 2: Introduction to NumPy |
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Exercise 2: Introduction to NumPy Solutions |
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| K-Nearest Neigbors and K-Means |
K-Nearest Neighbors |
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Recorded Lecture 20/21: kNN |
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Exercise 3: kNN |
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Exercise 3: kNN Solutions |
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K-Means Clustering |
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Recorded Lecture 20/21: K-Means |
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Exercise 4: K-Means |
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Exercise 4: K-Means Solutions |
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| Linear Regression and Classification |
Linear Regression |
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Linear Classification |
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Recorded Lecture 20/21: Linear Classification (1) |
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Recorded Lecture 20/21: Linear Classification (2) |
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Exercise 5: Logistic Regression |
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Exercise 5: Logistic Regression Solutions |
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Max Margin Classifiers |
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Recorded Lecture 20/21: Max-Margin Classifiers |
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| Non Linear Classification |
AdaBoost |
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Support Vector Machines |
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Proof of Cover's Theorem (optional) |
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Recorded Lecture 20/21: Adaboost |
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Recorded Lecture 20/21: Linear SVMs |
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Recorded Lecture 20/21: Kernel SVMs |
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Exercise 6: SVM |
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Exercise 6: SVM Solutions |
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| Non Linear Optimization |
Optimization Basics |
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Recorded Lecture 20/21: Optimization Basics |
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| Decision Forests |
Decision Forests |
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Recorded Lecture 20/21: Decision Forests |
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| Neural Networks |
Multi Layer Perceptrons |
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Recorded Lecture 20/21: MLPs (1) |
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 Recorded Lecture 20/21: MLP (2) |
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Exercise 7: MLP |
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Exercise 7: MLP Solutions |
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Convolutional Neural Nets |
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Recorded Lecture 20/21: CNNs |
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Exercise 8: CNN |
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Exercise 8: CNN Solutions |
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Exercise 9: UNet |
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Exercise 9: UNet Solutions |
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Transformers |
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| Dimensionality Reduction |
Linear Dimensionality Reduction |
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Recorded Lecture 20/21: Linear Dimensionality Reduction (1) |
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Recorded Lecture 20/21: Linear Dimensionality Reduction (2) |
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Exercise 10: PCA |
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Exercise 10: PCA Solutions |
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Non Linear Dimensionality Reduction |
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Recorded Lecture 20/21: Nonlinear Dimensionality Reduction |
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| Recap |
Course Recap |
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Recorded Lecture 20/21: Course Recap |
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| Project |
Project Description Document |
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Dataset MS1: HASYv2 |
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Framework MS1 |
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Dataset MS2: HASYv2 (20 classes) |
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Framework MS2 |
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| Mock Exam |
Mock Exam |
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Mock Exam Solutions |
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| Exam Classrooms |
CE 1515 |
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CE 1 1 |
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CE 1 3 |
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