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Keyword: backpropagation

Article:David E. Rumelhart, Geoffrey E. Hinton & Ronald J. Williams17 Sept 2026
Classic Paper on Backpropagation: Learning Representations by Back-Propagating Errors
The research paper by David E. Rumelhart, Geoffrey E. Hinton, and Ronald J. Williams introduces the backpropagation learning procedure for neural networks, adjusting connection weights to minimize output error.
From Video: Building an LLM from Scratch: Neural Networks, Tokenization, and Transformers
AI & LLMs· Research
Video
Video:CURT10 Jul 2026
Building an LLM from Scratch: Neural Networks, Tokenization, and Transformers
CJ breaks down the inner workings of large language models using historical context and working code implementations. He guides through the evolution from rule-based chatbots to transformers, covering neural networks, Byte Pair Encoding, and vector embeddings.
AI & LLMs· Tutorial

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Knowledge Base

Classic Paper on Backpropagation: Learning Representations by Back-Propagating Errors

Building an LLM from Scratch: Neural Networks, Tokenization, and Transformers

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