Reference sheet I can look up anytime. 📄 Good for anyone who wants to understand DL mathematically. 🧮

Topics covered:
- Notation, Forward Prop & Backpropagation 🔃
- Activation Functions, Loss, Gradient Descent (Adam, RMSProp...) 📉
- CNNs, RNNs, GRUs, LSTMs 🧠
- Transformers and Self-Attention 🔄
- ML Strategy and Shape Reference Tables 📊

52 pages, free to download. ⬇️
GitHub: https://github.com/Jerry-0821/deep-learning-formula-cheatsheet

Hope it helps other students or anyone trying to understand the math behind deep learning! 🎓✨

https://t.me/MachineLearning9 😮