PyTorch Practical - Tranformer Encoder Design and Implementation With PyTorch

Описание: 🔍 Design, Code, and Visualize the Encoder Block of the Transformer Model | Complete Walkthrough & Implementation

In this video, we break down the Encoder Block of the Transformer architecture — the foundation of models like BERT, T5, and many state-of-the-art NLP systems. You’ll learn to design, implement, and visualize each component from the ground up.

🚀 What You'll Learn:
The internal structure of the Transformer Encoder
How Multi-Head Self-Attention works
The role of Layer Normalization and Residual Connections
Building the Encoder Block in Python (PyTorch/TensorFlow)
Clear, step-by-step visualizations to boost your intuition

📌 This tutorial is perfect for anyone looking to understand transformers beyond the theory and get their hands dirty with code.

💻 Full Code Included:
No copy-paste black boxes — we build everything together from scratch so you know exactly how it works.

👉 If you find this helpful, be sure to like, subscribe, and tap the notification bell so you don’t miss upcoming videos on attention, transformers, and neural networks.

#Transformer, #EncoderBlock, #DeepLearning, #MachineLearning, #AI, #NeuralNetworks, #NLP, #AttentionIsAllYouNeed, #KindsonMunonye, #PyTorch, #TensorFlow

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