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165 - Transformer Architecture — Complete Introduction
Deep dive into patterns and axioms.
166 - Self-Attention and QKV Computation
Deep dive into patterns and axioms.
167 - Multi-Head Attention Deep Dive
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168 - Positional Encoding — Sinusoidal and Learned Embeddings
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169 - Decoder Layer, Cross-Attention, and Teacher Forcing
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170 - Layer Normalization & Residual Connections in Transformers
Deep dive into patterns and axioms.
171 - Pre-training Objectives- Causal LM, Masked LM, and Beyond
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172 - GPT Architecture- Decoder-Only Transformer & Autoregressive Generation
Deep dive into patterns and axioms.
173 - BERT Architecture- Encoder-Only & Bidirectional Context
Deep dive into patterns and axioms.
174 - Tokenization- BPE, WordPiece, SentencePiece
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175 - Fine-tuning Methods- LoRA, Adapters, and PEFT
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176 - Prompt Engineering- In-Context Learning, Chain-of-Thought
Deep dive into patterns and axioms.
177 - RLHF, Alignment, and Constitutional AI
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178 - Quantization, Pruning, Distillation & Fast Attention
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