Attention Is All You Need - Transformers
🚀 Transformers Explained – “Attention Is All You Need” Paper
In this video, I break down one of the most influential research papers in AI: Attention Is All You Need (Vaswani et al., 2017) – the work that introduced the Transformer architecture, the foundation for modern NLP models like BERT, GPT, and T5.
We’ll cover:
🔹 The problem with RNNs & CNNs for sequence modeling
🔹 How self-attention works (Scaled Dot-Product Attention & Multi-Head Attention)
🔹 The Transformer’s encoder-decoder structure
🔹 Positional encoding & why it’s needed
🔹 Results that set new benchmarks in translation and parsing
By the end, you’ll understand why this paper revolutionized deep learning and how it paved the way for today’s large language models.
📄 Original Paper: https://arxiv.org/abs/1706.03762
💻 Code (Tensor2Tensor): https://github.com/tensorflow/tensor2...
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