Schedule
The schedule is subject to change. Check back often. Notes/codes/slides links are placeholders for future lectures. They will be updated no later than the lecture date.
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EventDateDescriptionCourse Material
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Lecture01/18/2024
Thursday01 - Intro to Deep Learning and Course LogisticsUnfortunately the recording failed for this lecture. Will re-record it at some point.
Suggested Readings:
- UDL Chapter 1
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Lecture01/23/2024
Tuesday02 - Supervised LearningSuggested Readings:
- UDL Chapter 2
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Assignment01/23/2024
TuesdayPS2 -- Supervised Learning released! -
Discussion01/24/2024
WednesdayDiscussion_01 - Environment Setup and an Intro to Pytorch, Tensors, and Tensor Operations[slides]Notebook: 00_fundamentals.ipynb
Suggested Readings: -
Lecture01/25/2024
Thursday03 - Shallow NetworksSuggested Readings:
- UDL Chapter 3
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Assignment01/25/2024
ThursdayPS3 -- Shallow Networks released! -
Assignment01/29/2024
MondayProject Proposal released! -
Lecture01/30/2024
Tuesday04 - Deep NetworksSuggested Readings:
- UDL Chapter 4
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Assignment01/30/2024
TuesdayPS4 -- Deep Networks released! -
Due01/30/2024 23:59
TuesdayPS2 due -
Discussion01/31/2024
WednesdayDiscussion_02 - Autograd, and Computational Graphs in Pytorch. Intro to Model Building in Pytorch.Notebook: 01_autograd.ipynb
Suggested Readings: -
Lecture02/01/2024
Thursday05 - Loss FunctionsSuggested Readings:
- UDL Chapter 5
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Assignment02/01/2024
ThursdayKC5 -- Loss Functions released! -
Due02/01/2024 23:59
ThursdayPS3 due -
Lecture02/06/2024
Tuesday06 - Fitting ModelsSuggested Readings:
- UDL Chapter 6
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Due02/06/2024 23:59
TuesdayPS4 due -
Discussion02/07/2024
WednesdayDiscussion_03 - Intro to Model Training in Pytorch. (Image Classification, Text Classifcation)Notebook: 02_intro_nn_training.ipynb
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Lecture02/08/2024
Thursday07a - Gradients and BackpropagationSuggested Readings:
- UDL Sections 7.1 - 7.4
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Due02/08/2024 23:59
ThursdayKC5 due -
Discussion02/14/2024
WednesdayDiscussion_04 - Deep Dive 1: How to read, load, and process data. (Examples on Object Detection, Deep Learning on Tabular Data). Using GPUs on SCC. -
Lecture02/15/2024
Thursday07b - InitializationSuggested Readings:
- UDL Sections 7.5 - 7.6
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Due02/16/2024 23:59
FridayProject Proposal Due -
Assignment02/20/2024
TuesdayKC6-9 -- Chapters 6-9 Knowledge Checks released! -
Lecture02/20/2024
Tuesday08 - Measuring PerformanceSuggested Readings:
- UDL Chapter 8
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No Discussion Session02/21/2024 20:30
WednesdaySubstitute Monday schedule -
Lecture02/22/2024
Thursday09 - RegularizationSuggested Readings:
- UDL Chapter 9
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Due02/26/2024 23:59
MondayKC6-9 due -
Lecture02/27/2024
Tuesday10 - Convolutional Neural NetworksSuggested Readings:
- UDL Chapter 10
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Lecture02/29/2024
Thursday11 - Residual Networks[slides]Unfortunately the lecture recording cut off after 1 minute. I will try to re-record it at some point.
Suggested Readings:
- UDL Chapter 11
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Lecture02/29/2024
Thursday11a - Recurrent Neural NetworksSuggested Readings:
- UDL Chapter 11
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Lecture03/05/2024
Tuesday12 - TransformersSuggested Readings:
- UDL Chapter 12
- Optional The Illustrated Transformer
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Discussion03/06/2024
WednesdayDiscussion_05 - Deep Dive 2: Deep Learning Modules in Pytorch (CNN, RNN/LSTM, Transformer)Github Link: disc5
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Lecture03/07/2024
Thursday13 - Transformers Part 2Suggested Readings:
- UDL Chapter 12
- Optional The Illustrated Transformer
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Session Ends03/08/2024 20:30
FridayFirst 7 week session ends -
Start of Spring Recess03/09/2024 20:30
SaturdaySpring recess begins -- Have a great break! -
End of Spring Recess03/17/2024 20:30
SundaySpring recess ends -
Session Begins03/18/2024 20:30
Monday2nd 7 week session begins -
Lecture03/19/2024
Tuesday14 -- Vision & Multimodal TransformersSuggested Readings:
- See slides for references
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Discussion03/20/2024
WednesdayDiscussion_06 - Deep Dive 3: Logging, Model Checkpointing, Tracking Experiments, etc. Hyperparameter Tuning/Search (Optuna). Walkthrough of the VizWiz (Midterm Project) codebase.Github Link: disc6
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Lecture03/21/2024
Thursday15 -- Improving LLM PerfSuggested Readings:
- See slides for references
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Lecture03/26/2024
Tuesday16 - Parameter Efficient Fine TuningSuggested Readings: References are in the lecture slides.
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Discussion03/27/2024
WednesdayDiscussion_07 - Midterm Project Lab Session -
Discussion04/03/2024
WednesdayDiscussion_08 - Huggingface, ViT, CLIP, Kosmos2Github Link: disc8
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Lecture04/04/2024
Thursday17 -- Unsupervised Learning and GANsSuggested Readings:
- UDL Chapters 14 and 15
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Lecture04/09/2024
Tuesday18 - Variational Autoencoders (VAEs)[slides]Suggested Readings:
- Understanding Variational Autoencoders
- UDL Chapter 17 (optional)
Unfortunately the lecture recorded with no sound, so there is no lecture recording.
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Discussion04/10/2024
WednesdayDiscussion_09 - VAEs, and GANsGithub Link: disc9
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Lecture04/11/2024
Thursday19 -- Diffusion ModelsSuggested Readings:
- Rocca, Understanding Diffusion Probabilistic Models
- UDL Chapter 18
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Lecture04/16/2024
Tuesday20 -- Graph Neural NetworksSuggested Readings:
- UDL Chapter 13
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Lecture04/23/2024
Tuesday21 - Reinforcement Learning[slides]Suggested Readings:
- UDL Chapter 19
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Due04/25/2024 20:30
ThursdayProject Presentations Round 1 -
Due04/30/2024 20:30
TuesdayProject Presentations Round 2