Announcements
- Please check out the FAQ for a list of changes to the course for the remote offering.
- Please join piazza during the first week. This is where the majority of course announcements will be found.
Syllabus
Event | Date | In-class lecture | Online modules to complete | Materials and Assignments |
---|---|---|---|---|
Lecture 1 | 01/14 |
Topics: (slides)
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No online modules. If you are enrolled in CS230, you will receive an email on 01/13 to join Course 1 ("Neural Networks and Deep Learning") on Coursera with your Stanford email. | No assignments. |
Neural Networks and Deep Learning (Course 1) | ||||
Lecture 2 | 01/21 | Topics: Deep Learning Intuition (slides) | Completed modules:
Optional Video
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Quizzes (due at 8 30am PST):
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Project Meeting #1 | 01/29 Friday 11:59 PM | Instructions | Meet with any TA between 1/14 and 1/29 to discuss your proposal. | |
Project Proposal Due | 01/29 Friday 11:59 PM | Instructions | ||
Lecture 3 | 01/28 | Topics: Full-cycle of a Deep Learning Project (no slides) | Completed modules: |
Quizzes (due at 8 30am PST):
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Improving Deep Neural Networks: Hyperparameter tuning, Regularization and Optimization (Course 2) | ||||
Lecture 4 | 02/04 |
Topics: Adversarial examples - GANs (slides)
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Completed modules: |
Quizzes (due at 8 30am PST):
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Structuring Machine Learning Projects (Course 3) | ||||
Lecture 5 | 02/11 | Topics: AI and Healthcare. Guest Speaker: Pranav Rajpurkar. (guest slides) (main slides) | Completed modules: |
Quizzes (due at 8 30am PST):
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Convolutional Neural Networks (Course 4) | ||||
Midterm Review | TBA | Past midterms:
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Midterm | 02/17 | Time: 3 hours
Details TBA |
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Lecture 6 | 02/18 |
Topics: Deep Learning Strategy (no slides)
Optional Reading: A guide to convolution arithmetic for deep learning, Is the deconvolution layer the same as a convolutional layer?, Visualizing and Understanding Convolutional Networks, Deep Inside Convolutional Networks: Visualizing Image Classification Models and Saliency Maps, Understanding Neural Networks Through Deep Visualization, Learning Deep Features for Discriminative Localization |
Completed modules: |
Quizzes (due at 8 30am PST):
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Lecture 7 | 02/25 | Topics: Interpretability of Neural Networks (slides) | Completed modules: |
Quizzes (due at 8 30am PST):
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Project Meeting #2 | 02/26 Friday 11:59 PM | Instructions | Meet with your assigned TA between 1/28 and 2/26 to discuss your milestone report. | |
Project Milestone Due | 02/26 Friday 11:59 PM | Instructions | ||
Sequence Models (Course 5) | ||||
Lecture 8 | 03/04 |
Topics:
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Completed modules:
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Quizzes (due at 8 30am PST):
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Lecture 9 | 03/11 |
Topics:
(slides)
Optional Reading: |
Completed modules: |
Quizzes (due at 8 30am PST):
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Lecture 10 | 03/18 |
Topics: (slides)
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Optional:
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Project Meeting #3 | 03/18 Thursday 11:59 PM | Instructions | Meet with your assigned TA between 2/27 and 3/18 (before class) to discuss your final project report. | |
Project Final Report & Video Due | 03/18 Thursday 11:59 PM | Instructions | Please read over the final project guidelines here for information on the rubric and late submissions. |