index.md

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title	MATH 80600A - Machine Learning II<br>Deep Learning and Applications
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team	name url title image Jian Tang https://jian-tang.com/ Instructor assets/images/jian_tang.jpg name url title image Shengchao Liu https://chao1224.github.io/ Teaching Assistant assets/images/shengchao_liu.jpeg name url title image Louis-Pascal Xhonneux https://sites.google.com/a/mila.quebec/louis-pascal-xhonneux/home Teaching Assistant assets/images/louis_pascal_xhonneux.jpeg

Information

• Instructor: Jian Tang
• Trimester: Winter 2021
• When:
  • Class 1: 8:30 - 11:30 AM EST, Thursday
  • Class 2: 3:30 - 6:30 PM EST, Friday
• Where:
  • Zoom
• Office hour:
  • Jian Tang (Instructor): 2:00 - 3:00 PM EST, Friday
  • Shengchao Liu (TA): 10:00 - 11:00 AM EST, Friday
  • Louis-Pascal Xhonneux (TA): 10:00 - 11:00 AM EST, Friday

Objectives

• Understand machine learning basics
• Understand deep learning basics such as feedforward neural networks, convolutional neural networks, and recurrent neural networks
• Know several advanced topics in deep learning, including applications in natural language understanding, graph representation learning, recommender systems, and deep generative models
• Learn to use PyTorch for applying deep learning techniques to solve real-world problems

Prerequisites

• Linear algebra
• Python programming language
• One of following courses
  • Machine Learning I: Large-scale machine learning and decision making
  • Data Mining

Evaluation

• Homework: 20%
• Class Presentations: 10%
• Course Projects: 40%
  • Research Proposal: 5%
  • Poster: 10%
  • Report: 25%
• Final Exam: 30%

Staff

{% include team.html id="team" %}