architecture explained

The 15 most recent episodes and tracks on this topic.

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L15: Pre-training & fine tuning | gpt architecture adaptation & text generationIntroduction to large language models Notes
L14: Causal language modelling | decoder only transformers & autoregressive text generationIntroduction to large language models Notes
L13: Transformers for language modelling | encoder only decoder only & encoder decoder architecturesIntroduction to large language models Notes
L11: Language modelling | pre training foundation for large language modelsIntroduction to large language models Notes
L12: Introduction to language modelling - motivation | fine tuning in GPT & transformersIntroduction to large language models Notes
L10: Layer normalization | normalization in transformers encoder decoder architecture explainedIntroduction to large language models Notes
L8: Batch normalization | residual connections and layer normalization in transformersIntroduction to large language models Notes
L5: Sinusoidal encoding & sequence orderIntroduction to large language models Notes
L6: Zooming into decoder layer | decoding transformers masked self attention &cross attentionIntroduction to large language models Notes
L7: Positional encoding motivation methods & limitationsIntroduction to large language models Notes
L9: Teacher forcing & masked attention | autoregressive decoding with masking in transformersIntroduction to large language models Notes
L4: Multi-headed attention in transformers explainedIntroduction to large language models Notes
L3: Self-attention in transformers encoder & contextual word embeddingsIntroduction to large language models Notes
L2: Attention is all you need transformer architecture explainedIntroduction to large language models Notes
L1: Introduction to transformer architectureIntroduction to large language models Notes

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