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M1a Vector
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ccckmit edited this page
May 22, 2023
·
1 revision
Vectors In Transformer Neural Networks
Wiki pages
Pages
97
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Home
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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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Show 82 more pages…
GPT 背後的數學與程式
簡介
十分鐘看懂現代AI
梯度下降法
專案:NumGrad
反傳遞算法
專案:MicroGrad
GPT
RNN 循環神經網路
專案:MinGPT
ChatGPT
大語言模型
專案:llm.c
專案:llama2.c
llama3
提示工程學
補充
專案:MacroGrad
專案:MinRNN
損失函數
幻覺
Manifold 假說
向量資料庫
Softmax 與 CrossEntropy
詞向量
Embed 層
Seq2seq 模型
智慧突然湧現?
卷積神經網路CNN
從Sigmoid到ReLU
BPE分詞
多模態
從RLHF到DPO
Perplexity
KolmogorovComplexity
參考
思想遊戲
融合MCTS在LLM中
LLM 所造成的熵差異 -- 用模型做壓縮
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