ChengAo Shen
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These are my notes from the learning process, which I revisit from time to time. If they can be helpful to you, that would be absolutely wonderful for me.

13 posts 18 tags 2022–2026

2026

  1. 📚 Reading Note for LLM Wiki How to organize the LLM knowledge base? LLM wikiAgent2 min read
  2. 🤝 OpenTelemetry GenAI The Common Standard for Agent Trajectories Agent8 min read

2025

  1. ✏️ Gumbel Softmax Differentiable discrete sampling via the Gumbel-Softmax reparameterization. deep-learningmath2 min read
  2. 📃 Different Normalization Comparing BatchNorm, LayerNorm, InstanceNorm, and GroupNorm with key papers. deep-learningnormalization6 min read

2024

  1. 📜 Notes on LaTeX formulas LaTeX cheat sheet of math fonts, Greek letters, and useful symbols. latexwriting3 min read
  2. 🤗 Introduction to Generative Models Taxonomy of generative models: VAEs, GANs, flows, and diffusion. deep-learninggenerative-models3 min read
  3. ⚽️ Introduction to Prompt Engineering Core ideas of prompt engineering and how to talk effectively to LLMs. llmprompt-engineering4 min read

2023

  1. 📚 Using Custom Dataset in PyTorch Building Dataset and DataLoader for custom data in PyTorch. pytorchdeep-learning3 min read
  2. 💡 Introduction to Transformer Why Transformers work, walking through attention from first principles. deep-learningtransformernlp4 min read
  3. 📝 Common PyTorch Code Snippets Handy PyTorch snippets for device switching, layers, and training utilities. pytorchdeep-learningsnippets5 min read
  4. 🖊️ Effective Python Tips Pythonic best practices on style, expressions, and idiomatic patterns. pythontips14 min read

2022

  1. ⚕️ Brief introduction of the Tensor in PyTorch Initialization, attributes, and operations of PyTorch tensors. pytorchdeep-learning2 min read
  2. ✨ Organizing C Pointer Declarations A clear method to read and write complex C pointer declarations. cprogramming2 min read

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