L19.5.1 The Transformer Architecture @SebastianRaschka
L19.5.1 The Transformer Architecture  @SebastianRaschka
Uploaded May 2021 | Updated September 2026, 2 weeks ago
Sebastian's books: sebastianraschka.com/books

Slides: sebastianraschka.com/pdf/lecture-notes/stat453ss21/L19_seq2seq_rnn-transformers__slides.pdf

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This video is part of my Introduction of Deep Learning course.

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A handy overview page with links to the materials: sebastianraschka.com/blog/2021/dl-course.html

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L19.5.1 The Transformer ArchitectureL11.4 Why BatchNorm WorksL10.4 L2 Regularization for Neural NetsL13.9.2 Saving and Loading Models in PyTorchReinforcement Learning with Human Feedback (RLHF) in 4 minutesL19.5.2.5 GPT-v3: Language Models are Few-Shot LearnersL13.5 Whats The Difference Between Cross-Correlation And Convolution?L11.0 Input Normalization and Weight Initialization   Lecture OverviewBuild an LLM from Scratch 1: Set up your code environment13.3.2 Decision Trees & Random Forest Feature Importance (L13: Feature Selection)L13.9.1 LeNet-5 in PyTorchL17.4 Variational Autoencoder Loss Function
Sebastian Raschka |

L19.5.1 The Transformer Architecture

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