index.md

layout	title	permalink	team
default	MATH 80600A - Machine Learning II<br>Deep Learning and Applications	/	name url title image Jian Tang https://jian-tang.com/ Instructor assets/images/jian_tang.jpg name title image David Berger Teaching Assistant assets/images/shengchao_liu.jpeg name title image Andreea Deac Teaching Assistant assets/images/louis_pascal_xhonneux.jpeg

Information

• Instructor: Jian Tang
• Trimester: Winter 2022
• When:
  • Class 1 (in French): 3:30 - 6:30 PM EST, Wednesday
  • Class 2 (in English): 8:30 - 11:30 AM EST, Thursday
• Where:
  • Zoom
• Office hour:
  • Jian Tang (Instructor): TBA
  • Andreea Deac (TA): TBA
  • David Berger (TA): TBA

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" %}