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| title | MATH 80648A - Machine Learning II<br>Deep Learning | |||||||||||||||||||||||||||
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| team |
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- Instructor: Jian Tang
- Trimester: Fall 2025
- When:
- Class: 3:30 - 6:30 PM EST, Monday
- Exception: 3:30 - 6:30 PM EST, Wednesday on Oct.15
- Where:
- C-Ste-Cath, Caracas
- Office hour:
- Jian Tang (Instructor): TBD
- Zhihao Zhan (TA): TBD
- Xinyu Yuan (TA): TBD
- Discord:
- Join the discord for course discussion via this link
- Develop a basic understanding of machine learning principles.
- Learn the fundamentals of deep learning, including feedforward neural networks, convolutional neural networks, recurrent neural networks, and transformers.
- Explore advanced topics in deep learning, such as natural language understanding, graph representation learning, deep generative models.
- Gain experience using PyTorch to apply deep learning techniques to solve practical problems.
- Homework: 20%
- Class Presentations: 10%
- Course Projects: 30%
- Research Proposal: 5%
- Poster: 10%
- Report: 15%
- Final Exam: 40%
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