I. Class info：
Classroom: Featheringill Hall 132 TA Office hour: Featheringill Hall 333 Monday 9:30 AM - 11:30 PM, Yuechen Yang; Zoom Link Wednesday 1:00 PM - 3:00 PM, Yuechen Yang; Zoom Link Faculty Office hour: Friday 1:00 PM – 2:00 PM, FGH376 or Zoom (*Please reserve before Thursdays) Friday 1:00 PM at Zoom Link
II. Course Information：
Provides students with an understanding of conceptual and practical aspects of models and algorithms used in deep learning. Key topics covered in this course include: Basic mathematical tools and machine learning concepts used in deep learning; Modern practical deep feedforward, convolutional, and recurrent networks; Regularization for deep learning; Optimization for learning deep models; Practical design methods
III. Teaching Team:
Instructor: Yuankai Huo, yuankai.huo@vanderbilt.eduTA: Yuechen Yang, yuechen.yang@vanderbilt.edu Grader: Jiayi Xu
IV. Time:
Class Meets: Tuesday & Thursday, 02:45pm - 04:00pm, FGH 132
V. Useful links:
Course Website: https://hrlblab.github.io/CS4267.html
Submission & Discussion: https://www.vanderbilt.edu/brightspace
Schedule
|
Date |
Topics |
Comments |
|---|---|---|
| Jan 07 | Overview | all slides |
| Jan 09 | Introduction of deep learning | all homework |
| Jan 14 | From linear regression to deep learning | HW0 due |
| Jan 16 | From logistic regression to deep learning | |
| Jan 21 | Neural network | |
| Jan 23 | Neural network optimization | |
| Jan 28 | Machine learning basics | HW1 due |
| Jan 30 | Deep neural network | |
| Feb 04 | Final project proposal 1 | Project definition due |
| Feb 06 | Optimization | HW2 due |
| Feb 11 | Adaptive Learning Rate | Quiz 1 |
| Feb 13 | Final project proposal 2 | |
| Feb 18 | Mid-term Exam (in-class) | 90 mins in-person |
| Feb 20 | PyTorch and AutoGrad | Mini project proposal due |
| Feb 25 | Convolution | Mid-term Exam (take-home due) |
| Feb 27 | Convolutional Neural Network | HW3 due |
| Mar 04 | Computer Vision | |
| Mar 06 | Generative Model | Quiz 2 |
| Mar 11 | === Spring break === | |
| Mar 13 | === Spring break === | |
| Mar 18 | NLP | |
| Mar 20 | Self-attention | HW4 due |
| Mar 25 | Transformer | |
| Mar 27 | Transformer2 | |
| Apr 01 | Advanced Topics: HuggingFace & RL Intro | |
| Apr 03 | Advanced Topics: Reinforcement Learning | HW5 due |
| Apr 08 | Advanced Topics: Self-supervised Learning | presentation format |
| Apr 10 | Advanced Topics: RNN+LSTM | |
| Apr 15 | Advanced Topics: Stable Diffusion | |
| Apr 17 | Summary | Quiz 3 |
| Apr 22 | (no class) | HW6 due |
| Apr 24 | Final presentation poster/report due (no class) | Final project due |
Assignments
|
Assignments |
Download |
Due Date |
|---|---|---|
| Mini Project Proposal | Example | Due 02/20/2025 9AM |
| Mini Project Presentation | Example | Due 04/24/2025 9AM |
Grading, Homework, Mid Term Exam, and Final Project
More details are provided Here.
Computational Resource
GPU computing is required for this class. All the homework should be done and submitted using Google Colab. You can use Colab or your own/lab’s GPU for the final project since that is the most convenient way of writing and testing code with GUI.
FAQs
1. The class is full. Can I still get in?
It is unlikely except other students drop it during the first week.
2. What is pre-requirement?
Linear algebra, programming in python, introduction in machine learning.
3. Can I sit in class without registering?
Yes after getting the instructor’s approval. Another option is to register to audit the class (just $50).
References
* We used images and contents in the slides from the following resources, thanks for the great work done by the smart people!
https://speech.ee.ntu.edu.tw/~tlkagk/courses.html
https://speech.ee.ntu.edu.tw/~hylee/index.php
http://cs231n.stanford.edu/
http://deeplearning.cs.cmu.edu/
https://www.deeplearningbook.org/lecture_slides.html
https://www.cs.princeton.edu/courses/archive/spring16/cos495/
http://ttic.uchicago.edu/~shubhendu/Pages/CMSC35246.html
https://speech.ee.ntu.edu.tw/~hylee/ml/2021-spring.php
https://speech.ee.ntu.edu.tw/~hylee/ml/2022-spring.php
https://speech.ee.ntu.edu.tw/~hylee/ml/2023-spring.php
https://www.cc.gatech.edu/classes/AY2018/cs7643_fall
http://introtodeeplearning.com/