RNN vs LSTM vs GRU vs Transformers | Deep Learning & NLP Architectures Explained

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Confused about RNNs, LSTMs, GRUs, and transformers? In this video, we'll break down the key differences between these popular sequence modeling techniques. We'll explore their strengths, weaknesses, and real-world applications.

Key Topics:
1. Recurrent Neural Networks (RNNs)
2. Long Short-Term Memory (LSTM) networks
3. Gated Recurrent Units (GRUs)
4. Transformer architecture
5. Comparison and contrast of these models
6. Evolution of sequence modeling techniques
7. Vanishing gradient problem
8. The power of attention mechanism
9. Transformer architecture and its components

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