📗 -> 03/31/25: Intro to Deep Learning
🎤 Vocab
❗ Unit and Larger Context
Weeder Philosophy:
- Knowledge > Grade
- Heavy workload
- Self-learning
✒️ -> Scratch Notes
Topics Covered:
DL Background:
- Intro
- Basics
- Optimization
DL Prelims - DL basics
- MLP (multi layer perceptron)
- Autoencoder
DL for Image - CNN
- Computer Vision
- GAN
Midterm Split
DL for Text
- RNN, LSTM
- NLP & Text Embedding
- Transformer, BERT
DL for Graph - GNN
- Network Embedding
- Graph-BERT
🧪 -> Refresh the Info
Did you generally find the overall content understandable or compelling or relevant or not, and why, or which aspects of the reading were most novel or challenging for you and which aspects were most familiar or straightforward?)
Did a specific aspect of the reading raise questions for you or relate to other ideas and findings you’ve encountered, or are there other related issues you wish had been covered?)
🔗 -> Links
Resources
- Put useful links here
Connections
- Link all related words