Neural Netwrks & Deep Learning
10:10am–12:40pm
MATHEMATICS BUILDING MAT 207
Morningside
Seat data provenance: Directory as of August 23, 2026 at 4:00 AM
Description
Lect: 3. Developing features - internal representations of the world, artificial neural networks, classifying handwritten digits with logistics regression, feedforward deep networks, back propagation in multilayer perceptrons, regularization of deep or distributed models, optimization for training deep models, convolutional neural networks, recurrent and recursive neural networks, deep learning in speech and object recognition
Reviews
Course experience
n=4, 2024–2026
Aggregated across everyone who has taught this course.
Teaching quality
3.6 / 5
Grading fairness
No signal
Workload
No signal
Difficulty
3.0 / 5 · Moderate
Overall sentiment
Positive
Would take again
Majority say yes
Sources: CULPA (4)
In your week
Where it meets
Flat map — motion reduced
Workload and grading
- Grading
- Not published
- Format
- Not published
- Credits
- 3 credits
Reported workload
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