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Part 7: Multimodal Learning

Part 1: Deep Learning Fundamentals
- Chapter 1: Introduction to Deep Learning
  - 1.1 Neural Networks: A Learnable Function
  - 1.3 Forward Propagation, Backpropagation, and Computation Graph
- Chapter 2: Getting Started with PyTorch
  - 2.1 Automatic Differentiation in PyTorch
  - 2.2 Gradient Recording and Control in PyTorch
Part 4: Attention Mechanism and Transformer
- Chapter 8: Attention and Transformer: From Dynamic Retrieval to Sequence Modeling
- Chapter 10: Efficient Attention Implementations: From Memory-Efficient Attention to FlashAttention
  - 10.1 Why Attention is IO-Bound
  - 10.2 Flash Attention v1: Eliminating the IO Bottleneck in Attention Mechanisms
Part 6: Generative Models
Part 7: Multimodal Learning
- Chapter 15: Vision-Language Models: From Image-Text Alignment to Multimodal Dialogue
  - 15.1 CLIP: Connecting Images and Language with Contrastive Learning

Part 7: Multimodal Learning

Author

jshn9515

Published

2026-05-05

Modified

2026-05-21

Title	Author	Date
15.1 CLIP: Connecting Images and Language with Contrastive Learning	jshn9515	2026-04-07

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