Page Index - cccbook/py2gpt GitHub Wiki

195 page(s) in this GitHub Wiki:

• Home
• GPT 背後的數學與程式
• 補充
• 00 前言與目錄
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• 01 深度學習簡介
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• 02 訓練算法
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• 02a 梯度下降法
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• 02a1 自製梯度下降法
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• 02b 微分與梯度
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• 02c 梯度下降法2
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• 02d 反傳遞演算法
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• 02d1 自製反傳遞演算法
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• 02e1 Softmax的反傳遞數學公式
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• 02e2 CrossEntropy 的反傳遞數學公式
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• 02e3 最小平方法的反傳遞公式
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• 03 語言模型與RNN
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• 03a 詞向量
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• 03b AutoEncoder
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• 03c embed層
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• 03d RNN循環神經網路
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• 04 Transformer
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• 04a 向ChatGPT學Transformer
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• 04b1 Attention的意義
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• 04b2 Attention的實作
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• 04b3 Attention的數學與意義
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• 04c Pytorch中的Transformer
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• 04c Transformer實作
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• 04f BERT
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• 05 GPT
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• 05a 向ChatGPT學GPT
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• 05a1 GPT1
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• 05a2 GPT2
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• 05a3 GPT3
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• 05b ChatGPT
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• 05c OpenAi的API
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• 05d minGPT
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• 06 深度學習應用
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• 06a 影像生成
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• 06a1 GAN
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• 06a2 VAE
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• 06a3 diffusion
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• 06b 影像識別
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• 06b1 CNN卷積神經網路
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• 06c 音樂作曲
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• 06d 下棋
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• 07 深度學習未來
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• A1 本書的撰寫方法
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• A9 nanoGPT
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• ai10min
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• backProp
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• backProp2
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• bpe
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• ChatGpt
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• cnn
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• embed
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• embed2
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• emerging
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• encoderDecoder
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• entropy
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• gpt
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• gpt1
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• gpt2
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• grad
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• hallucination
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• introduction
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• KolmogorovComplexity
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• llama3
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• llm
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• llm_entropy
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• llmBookNote
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• loss
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• loss2
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• M1 數學背景
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• M1a Vector
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• M1c Activation
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• M2 優化
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• M2a Loss
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• M2b Optimizer
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• M2c Batch
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• M3 機率統計
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• M3a 最大似然估計
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• manifoldHypothesis
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• mcts_llm
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• micrograd
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• multimodel
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• Perplexity
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• prompt
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• R1 深度學習參考文獻
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• R2 用迭代法訓練神經網路
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• reference
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• relu
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• rlhf_dpo
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• rnn
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• seq2seq
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• softmax
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• TheOnePieceInLLM
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• vectorDatabase
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• word2vector
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• wordVector
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