Week 1 |
Introduction |
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K-Nearest Neighbors |
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Recorded Lecture 1: Introduction and kNN |
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Exercise 1: Introduction to Python |
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Exercise 1: Introduction to Python - SOLUTIONS |
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Python Cheatsheet |
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Matplotlib Cheatsheet |
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Week 2 |
Recorded Lecture 2: kNN |
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Recorded Lecture 2: Python |
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Python and NumPy Primer |
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Exercise 2: Introduction to NumPy |
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Exercise 2: Introduction to NumPy - SOLUTIONS |
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NumPy Cheatsheet |
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Week 3 |
K-Means Clustering |
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Linear Classification |
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Exercise 3: KNN |
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Exercise 3: KNN - SOLUTIONS |
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Recorded Lecture 3: K-Means |
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Recorded Lecture 3: Linear Classification |
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Week 4 |
Linear Classification (continued) |
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Recorded Lecture 4: Linear Classification (continued) |
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Max Margin Classifiers |
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Exercise 4: K means |
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Recorded Lecture 4: Max-Margin Classifiers |
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Exercise 4: K means Solutions |
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Week 5 |
Recorded Lecture 5: Optimization Basics |
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Optimization Basics |
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Exercise 5: Logistic Regression |
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Exercise 5: Logistic Regression Solutions |
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Week 6 |
AdaBoost |
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Recorded Lecture: Adaboost |
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Support Vector Machines |
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Recorded Lecture: SVM |
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Exercise 6: Linear SVM |
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Exercise 6: Linear SVM Solutions |
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Week 7 |
Support Vector Machines (continued) |
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Recorded Lecture: Kernel SVM |
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Proof of Cover's Theorem (optional) |
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Exercise 7: Kernel SVM |
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Exercise 7: Kernel SVM Solutions |
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Week 8 |
Multi Layer Perceptrons |
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Recorded Lecture: MLPs |
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Exercise 8: MLPs |
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Exercise 8: MLPs Solutions |
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Week 9 |
Multi Layer Perceptrons (continued) |
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Recorded Lecture: MLP continued |
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Mock Exam |
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Mock Exam Solutions |
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Week 10 |
Convolutional Neural Nets |
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Exercise 9: CNNs |
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Exercise 9: CNNs Solutions |
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Recorded Lecture: CNNs |
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Week 11 |
Linear Dimensionality Reduction |
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Recorded Lecture: Linear Dimensionality Reduction |
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Alpha Go |
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Recorded Lecture: Alpha Go |
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Exercise 10: U-Net |
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Exercise 10: U-Net Solutions |
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Week 12 |
Non Linear Dimensionality Reduction |
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Exercise 11: Linear Dimensionality Reduction |
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Exercise 11: Linear Dimensionality Reduction Solutions |
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Recorded Lecture: Linear Dimensionality Reduction Part 2 |
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Recorded Lecture: Nonlinear Dimensionality Reduction |
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Week 13 |
Decision Forests |
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Recorded Lecture: Decision Forests |
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Shape Design |
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Recorded Lecture: Shape Design |
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Exercise 12: Autoencoders |
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Exercise 12: Autoencoders Solutions |
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Week 14 |
Course Recap |
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Recorded Lecture: Review Session |
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