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MATH 60630A - Machine Learning II<br>Deep Learning
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Jian Tang
Instructor
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Jianan Zhao ([email protected])
Teaching Assistant
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Xinyu Yuan ([email protected])
Teaching Assistant
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Information

  • Instructor: Jian Tang
  • Trimester: Fall 2024
  • When:
    • Class 1: 3:30 - 6:30 PM EST, Monday
    • Class 2: 8:30 - 11:30 AM EST, Friday
  • Where:
    • Zoom
  • Office hour:
    • Jian Tang (Instructor): 2:00 - 3:00 PM EST, Friday
    • Jianan Zhao (TA): 10:00 - 11:00 AM EST, Thursday
    • Xinyu Yuan (TA): 10:00 - 11:00 AM EST, Friday
  • Discord:
    • Join the discord for course discussion via this link

Objectives

  • 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.

Evaluation

  • Homework: 20%
  • Class Presentations: 10%
  • Course Projects: 30%
    • Research Proposal: 5%
    • Poster: 10%
    • Report: 15%
  • Final Exam: 40%

Staff

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