10-301 + 10-601, Fall 2024
School of Computer Science
Carnegie Mellon University
This schedule is tentative and subject to change. Please check back often.
Date | Lecture | Readings | Announcements |
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Classification & Regression |
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Mon, 26-Aug | Lecture 1
:
Course Overview [Slides] [Slides (Inked)] |
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HW1 Out |
Wed, 28-Aug | Lecture 2
:
Machine Learning as Function Approximation [Slides] [Slides (Inked)] |
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Fri, 30-Aug |
Recitation: HW1 [Handout] [Solutions] |
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Mon, 2-Sep |
(Labor Day - No Class) |
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Wed, 4-Sep | Lecture 3
:
Decision Trees [Slides] [Slides (Inked)] [Poll] |
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HW1 Due HW2 Out |
Fri, 6-Sep |
Recitation: HW2 [Handout] [Solutions] |
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Mon, 9-Sep | Lecture 4
:
k-Nearest Neighbors [Slides] [Slides (Inked)] [Poll] |
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Wed, 11-Sep | Lecture 5
:
Model Selection and Experimental Design [Slides] [Slides (Inked)] [Poll] |
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Linear Models |
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Fri, 13-Sep | Lecture 6
:
Perceptron [Slides] [Slides (Inked)] [Poll] |
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Mon, 16-Sep | Lecture 7
:
Linear Regression [Slides] [Slides (Inked)] [Poll] |
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HW2 Due HW3 Out |
Wed, 18-Sep | Lecture 8
:
Optimization for ML [Slides] [Slides (Inked)] [Poll] |
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Fri, 20-Sep |
Recitation: HW3 [Handout] [Solutions] |
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Exam 1 Practice Problems out |
Mon, 23-Sep | Lecture 9
:
Stochastic Gradient Descent / Logistic Regression [Slides] [Slides (Inked)] [Poll] |
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HW3 Due (only two grace/late days permitted)
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Wed, 25-Sep | Lecture 10
:
Feature Engineering / Regularization [Slides] [Slides (Inked)] [Poll] |
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Fri, 27-Sep |
Exam 1 Review OH |
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Neural Networks |
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Mon, 30-Sep | Lecture 11
:
Neural Networks [Slides] [Slides (Inked)] [Poll] |
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Mon, 30-Sep |
Exam 1 (evening exam, details will be announced on Piazza) 6:30p - 8:30p |
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HW4 Out |
Wed, 2-Oct | Lecture 12
:
Backpropagation I [Slides] [Slides (Inked)] [Poll] |
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Fri, 4-Oct |
Recitation: HW4 [Handout] [Solutions] |
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Mon, 7-Oct | Lecture 13
:
Backpropagation II [Slides] [Slides (Inked)] [Poll] |
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Societal Impacts |
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Wed, 9-Oct | Lecture 14
:
Societal Impacts of ML [Slides] [Slides (Inked)] [Poll] |
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HW4 Due HW5 Out |
Fri, 11-Oct |
Recitation: HW5 [Handout] [Solutions] |
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Mon, 14-Oct |
(Fall Break - No Class) |
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Tue, 15-Oct |
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Wed, 16-Oct |
(Fall Break - No Class) |
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Thu, 17-Oct |
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Fri, 18-Oct |
(Fall Break - No Class) |
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Learning Theory |
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Mon, 21-Oct | Lecture 15
:
PAC Learning [Slides] [Poll] |
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Wed, 23-Oct | Lecture 16
:
PAC Learning / MLE & MAP [Poll] |
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Fri, 25-Oct |
Recitation: HW6 |
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Sun, 27-Oct |
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HW5 Due HW6 Out, Exam 2 Practice Problems out |
Deep Learning |
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Mon, 28-Oct | Lecture 17
:
CNNs and RNNs [Poll] |
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Wed, 30-Oct | Lecture 18
:
RNN-LMs and Transformers-LMs [Poll] |
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Fri, 1-Nov |
Exam 2 Review OH |
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Sat, 2-Nov |
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HW6 Due (only two grace/late days permitted)
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Mon, 4-Nov | Lecture 19
:
AutoDiff, Pre-training, Fine-Tuning, In-context Learning [Poll] |
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Reinforcement Learning |
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Wed, 6-Nov | Lecture 20
:
Reinforcement Learning: MDPs [Poll] |
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Thu, 7-Nov |
Exam 2 (evening exam, details will be announced on Piazza) 6:30p - 8:30p |
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HW7 Out |
Fri, 8-Nov |
Recitation: HW7 |
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Mon, 11-Nov | Lecture 21
:
Reinforcement Learning: Value/Policy Iteration [Poll] |
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Wed, 13-Nov | Lecture 22
:
Reinforcement Learning: Q-Learning / Deep RL [Poll] |
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Fri, 15-Nov |
Recitation: HW8 |
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Sun, 17-Nov |
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HW7 Due HW8 Out |
Learning Paradigms |
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Mon, 18-Nov | Lecture 23
:
Dimensionality Reduction: PCA [Poll] |
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Wed, 20-Nov | Lecture 24
:
K-Means / Ensemble Methods: Bagging [Poll] |
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Fri, 22-Nov |
No Recitation |
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Mon, 25-Nov | Lecture 25
:
Ensemble Methods: Boosting / Recommender Systems [Poll] |
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HW8 Due HW9 Out |
Wed, 27-Nov |
(Thanksgiving Break - No Class) |
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Thu, 28-Nov |
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Fri, 29-Nov |
(Thanksgiving Break - No Class) |
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Mon, 2-Dec |
Recitation: HW9 |
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Exam 3 Practice Problems out |
Wed, 4-Dec | Lecture 26
:
Special Topics: Generative Models for Vision / Significance Testing for ML [Poll] |
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Thu, 5-Dec |
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HW9 Due (only two grace/late days permitted)
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Fri, 6-Dec |
Exam 3 Review OH |
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