2020/07/23
-----
Softmax
https://pojenlai.wordpress.com/2016/02/27/tensorflow%E8%AA%B2%E7%A8%8B%E7%AD%86%E8%A8%98-softmax%E5%AF%A6%E4%BD%9C/
-----
Thursday, July 23, 2020
Softmax
Softmax
2020/07/23
-----
Softmax
https://pojenlai.wordpress.com/2016/02/27/tensorflow%E8%AA%B2%E7%A8%8B%E7%AD%86%E8%A8%98-softmax%E5%AF%A6%E4%BD%9C/
-----
2020/07/23
-----
Softmax
https://pojenlai.wordpress.com/2016/02/27/tensorflow%E8%AA%B2%E7%A8%8B%E7%AD%86%E8%A8%98-softmax%E5%AF%A6%E4%BD%9C/
-----
WordRank
WordRank
2020/07/20
-----
References
Ji, Shihao, et al. "Wordrank: Learning word embeddings via robust ranking." arXiv preprint arXiv:1506.02761 (2015).
https://arxiv.org/pdf/1506.02761.pdf
WordRank embedding: “crowned” is most similar to “king”, not word2vec’s “Canute” | RARE Technologies
https://rare-technologies.com/wordrank-embedding-crowned-is-most-similar-to-king-not-word2vecs-canute/
2020/07/20
-----
References
Ji, Shihao, et al. "Wordrank: Learning word embeddings via robust ranking." arXiv preprint arXiv:1506.02761 (2015).
https://arxiv.org/pdf/1506.02761.pdf
WordRank embedding: “crowned” is most similar to “king”, not word2vec’s “Canute” | RARE Technologies
https://rare-technologies.com/wordrank-embedding-crowned-is-most-similar-to-king-not-word2vecs-canute/
fastText v2
fastText v2
2020/07/20
-----
References
Bojanowski, Piotr, et al. "Enriching word vectors with subword information." Transactions of the Association for Computational Linguistics 5 (2017): 135-146.
https://www.mitpressjournals.org/doi/pdfplus/10.1162/tacl_a_00051
Word Embedding Papers | 经典再读之fastText | 机器之心
https://www.jiqizhixin.com/articles/2020-07-03-14
【NLP论文笔记】Enriching word vectors with subword information（FastText词向量） - 简书
https://www.jianshu.com/p/e49b4777a068
2020/07/20
-----
References
Bojanowski, Piotr, et al. "Enriching word vectors with subword information." Transactions of the Association for Computational Linguistics 5 (2017): 135-146.
https://www.mitpressjournals.org/doi/pdfplus/10.1162/tacl_a_00051
Word Embedding Papers | 经典再读之fastText | 机器之心
https://www.jiqizhixin.com/articles/2020-07-03-14
【NLP论文笔记】Enriching word vectors with subword information（FastText词向量） - 简书
https://www.jianshu.com/p/e49b4777a068
fastText v1
fastText v1
2020/07/20
-----
References
Word Embedding Papers | 经典再读之fastText | 机器之心
https://www.jiqizhixin.com/articles/2020-07-03-14
笔记: Bag of Tricks for Efficient Text Classification
https://www.paperweekly.site/papers/notes/132
2020/07/20
-----
References
Word Embedding Papers | 经典再读之fastText | 机器之心
https://www.jiqizhixin.com/articles/2020-07-03-14
笔记: Bag of Tricks for Efficient Text Classification
https://www.paperweekly.site/papers/notes/132
GloVe
GloVe
2020/07/20
-----
https://pixabay.com/zh/photos/boxing-gloves-sport-pink-glove-415394/
-----
https://towardsdatascience.com/word-embeddings-for-nlp-5b72991e01d4
-----
References
◎ 英文
NLP — Word Embedding & GloVe. BERT is a major milestone in creating… | by Jonathan Hui | Medium
https://medium.com/@jonathan_hui/nlp-word-embedding-glove-5e7f523999f6
Word Vectors in Natural Language Processing: Global Vectors (GloVe) | by Sciforce | Sciforce | Medium
https://medium.com/sciforce/word-vectors-in-natural-language-processing-global-vectors-glove-51339db89639
NLP and Deep Learning All-in-One Part II: Word2vec, GloVe, and fastText | by Bruce Yang | Medium
https://medium.com/@bruceyanghy/nlp-and-deep-learning-all-in-one-part-ii-word2vec-glove-and-fasttext-184bd03a7ba
What is GloVe?. GloVe stands for global vectors for… | by Japneet Singh Chawla | Analytics Vidhya | Medium
https://medium.com/analytics-vidhya/word-vectorization-using-glove-76919685ee0b
Intuitive Guide to Understanding GloVe Embeddings | by Thushan Ganegedara | Towards Data Science
https://towardsdatascience.com/light-on-math-ml-intuitive-guide-to-understanding-glove-embeddings-b13b4f19c010
Word Embeddings for NLP. Understanding word embeddings and their… | by Renu Khandelwal | Towards Data Science
https://towardsdatascience.com/word-embeddings-for-nlp-5b72991e01d4
-----
◎ 簡中
GloVe详解 | 范永勇
http://www.fanyeong.com/2018/02/19/glove-in-detail/
GloVe:另一种Word Embedding方法
https://pengfoo.com/post/machine-learning/2017-04-11
CS224N NLP with Deep Learning（三）：词向量之GloVe - 知乎
https://zhuanlan.zhihu.com/p/50543888
NLP︱高级词向量表达（一）——GloVe（理论、相关测评结果、R&python实现、相关应用）_素质云笔记/Recorder...-CSDN博客_glove
https://blog.csdn.net/sinat_26917383/article/details/54847240
2.8 GloVe词向量-深度学习第五课《序列模型》-Stanford吴恩达教授_Jichao Zhao的博客-CSDN博客_glove单词表示的全局变量
https://blog.csdn.net/weixin_36815313/article/details/106633339
四步理解GloVe！(附代码实现) - 知乎
https://zhuanlan.zhihu.com/p/79573970
2020/07/20
-----
https://pixabay.com/zh/photos/boxing-gloves-sport-pink-glove-415394/
-----
https://towardsdatascience.com/word-embeddings-for-nlp-5b72991e01d4
-----
References
◎ 英文
NLP — Word Embedding & GloVe. BERT is a major milestone in creating… | by Jonathan Hui | Medium
https://medium.com/@jonathan_hui/nlp-word-embedding-glove-5e7f523999f6
Word Vectors in Natural Language Processing: Global Vectors (GloVe) | by Sciforce | Sciforce | Medium
https://medium.com/sciforce/word-vectors-in-natural-language-processing-global-vectors-glove-51339db89639
NLP and Deep Learning All-in-One Part II: Word2vec, GloVe, and fastText | by Bruce Yang | Medium
https://medium.com/@bruceyanghy/nlp-and-deep-learning-all-in-one-part-ii-word2vec-glove-and-fasttext-184bd03a7ba
What is GloVe?. GloVe stands for global vectors for… | by Japneet Singh Chawla | Analytics Vidhya | Medium
https://medium.com/analytics-vidhya/word-vectorization-using-glove-76919685ee0b
Intuitive Guide to Understanding GloVe Embeddings | by Thushan Ganegedara | Towards Data Science
https://towardsdatascience.com/light-on-math-ml-intuitive-guide-to-understanding-glove-embeddings-b13b4f19c010
Word Embeddings for NLP. Understanding word embeddings and their… | by Renu Khandelwal | Towards Data Science
https://towardsdatascience.com/word-embeddings-for-nlp-5b72991e01d4
-----
◎ 簡中
GloVe详解 | 范永勇
http://www.fanyeong.com/2018/02/19/glove-in-detail/
GloVe:另一种Word Embedding方法
https://pengfoo.com/post/machine-learning/2017-04-11
CS224N NLP with Deep Learning（三）：词向量之GloVe - 知乎
https://zhuanlan.zhihu.com/p/50543888
NLP︱高级词向量表达（一）——GloVe（理论、相关测评结果、R&python实现、相关应用）_素质云笔记/Recorder...-CSDN博客_glove
https://blog.csdn.net/sinat_26917383/article/details/54847240
2.8 GloVe词向量-深度学习第五课《序列模型》-Stanford吴恩达教授_Jichao Zhao的博客-CSDN博客_glove单词表示的全局变量
https://blog.csdn.net/weixin_36815313/article/details/106633339
四步理解GloVe！(附代码实现) - 知乎
https://zhuanlan.zhihu.com/p/79573970
LSA
LSA（Latent Semantic Analysis）
2020/07/22
-----
TF-IDF
https://towardsdatascience.com/latent-semantic-analysis-distributional-semantics-in-nlp-ea84bf686b50
-----
TF-IDF
https://medium.com/nanonets/topic-modeling-with-lsa-psla-lda-and-lda2vec-555ff65b0b05
-----
LSA1
https://www.analyticsvidhya.com/blog/2018/10/stepwise-guide-topic-modeling-latent-semantic-analysis/
-----
LSA2
https://www.analyticsvidhya.com/blog/2018/10/stepwise-guide-topic-modeling-latent-semantic-analysis/
-----
Term Co-occurrence Matrix
https://towardsdatascience.com/latent-semantic-analysis-deduce-the-hidden-topic-from-the-document-f360e8c0614b
-----
SVD
https://blog.csdn.net/weixin_42398658/article/details/85088130
-----
SVD
https://www.jianshu.com/p/9fe0a7004560
-----
SVD and LSA
https://blog.csdn.net/callejon/article/details/49811819
-----
2020/07/22
-----
TF-IDF
https://towardsdatascience.com/latent-semantic-analysis-distributional-semantics-in-nlp-ea84bf686b50
-----
TF-IDF
https://medium.com/nanonets/topic-modeling-with-lsa-psla-lda-and-lda2vec-555ff65b0b05
-----
LSA1
https://www.analyticsvidhya.com/blog/2018/10/stepwise-guide-topic-modeling-latent-semantic-analysis/
-----
LSA2
https://www.analyticsvidhya.com/blog/2018/10/stepwise-guide-topic-modeling-latent-semantic-analysis/
-----
Term Co-occurrence Matrix
https://towardsdatascience.com/latent-semantic-analysis-deduce-the-hidden-topic-from-the-document-f360e8c0614b
-----
SVD
https://blog.csdn.net/weixin_42398658/article/details/85088130
-----
SVD
https://www.jianshu.com/p/9fe0a7004560
-----
SVD and LSA
https://blog.csdn.net/callejon/article/details/49811819
-----
Saturday, July 18, 2020
RNNLM
RNNLM
2020/07/18
-----
-----
-----
References
RNNLM
Mikolov, Tomáš, Martin Karafiát, and Lukáš Burget. "Jan ˇCernocky, and Sanjeev Khudanpur. 2010. Recurrent neural network based language model." Eleventh annual conference of the international speech communication association. 2010.
https://www.fit.vutbr.cz/research/groups/speech/publi/2010/mikolov_interspeech2010_IS100722.pdf
RNNLM Extention
Mikolov, Tomáš, et al. "Extensions of recurrent neural network language model." 2011 IEEE international conference on acoustics, speech and signal processing (ICASSP). IEEE, 2011.
https://pdfs.semanticscholar.org/bba8/a2c9b9121e7c78e91ea2a68630e77c0ad20f.pdf
RNNLM Toolkit
Mikolov, Tomas, et al. "Rnnlm-recurrent neural network language modeling toolkit." Proc. of the 2011 ASRU Workshop. 2011.
http://www.fit.vutbr.cz/~imikolov/rnnlm/rnnlm-demo.pdf
2020/07/18
-----
-----
-----
References
RNNLM
Mikolov, Tomáš, Martin Karafiát, and Lukáš Burget. "Jan ˇCernocky, and Sanjeev Khudanpur. 2010. Recurrent neural network based language model." Eleventh annual conference of the international speech communication association. 2010.
https://www.fit.vutbr.cz/research/groups/speech/publi/2010/mikolov_interspeech2010_IS100722.pdf
RNNLM Extention
Mikolov, Tomáš, et al. "Extensions of recurrent neural network language model." 2011 IEEE international conference on acoustics, speech and signal processing (ICASSP). IEEE, 2011.
https://pdfs.semanticscholar.org/bba8/a2c9b9121e7c78e91ea2a68630e77c0ad20f.pdf
RNNLM Toolkit
Mikolov, Tomas, et al. "Rnnlm-recurrent neural network language modeling toolkit." Proc. of the 2011 ASRU Workshop. 2011.
http://www.fit.vutbr.cz/~imikolov/rnnlm/rnnlm-demo.pdf
C&W
C&W
2020/07/18
-----
-----
-----
-----
-----
-----
-----
References
// 英文資料
C&W
Collobert, Ronan, et al. "Natural language processing (almost) from scratch." Journal of machine learning research 12.ARTICLE (2011): 2493-2537.
http://www.jmlr.org/papers/volume12/collobert11a/collobert11a.pdf
// 英文投影片
NLP from scratch
https://www.slideshare.net/bryanzhanghang/nlp-from-scratch
// 英文投影片
PPT - Natural Language Processing PowerPoint Presentation, free download - ID:5753691
https://www.slideserve.com/bisa/natural-language-processing/
-----
// 日文資料
// 日文投影片
Natural Language Processing (Almost) from Scratch（第 6 回 Deep Learning…
https://www.slideshare.net/alembert2000/deep-learning-6
-----
// 簡中資料
读论文《Natural Language Processing from Scratch》 - 知乎
https://zhuanlan.zhihu.com/p/59744800
2020/07/18
-----
-----
-----
-----
-----
-----
-----
References
// 英文資料
C&W
Collobert, Ronan, et al. "Natural language processing (almost) from scratch." Journal of machine learning research 12.ARTICLE (2011): 2493-2537.
http://www.jmlr.org/papers/volume12/collobert11a/collobert11a.pdf
// 英文投影片
NLP from scratch
https://www.slideshare.net/bryanzhanghang/nlp-from-scratch
// 英文投影片
PPT - Natural Language Processing PowerPoint Presentation, free download - ID:5753691
https://www.slideserve.com/bisa/natural-language-processing/
-----
// 日文資料
// 日文投影片
Natural Language Processing (Almost) from Scratch（第 6 回 Deep Learning…
https://www.slideshare.net/alembert2000/deep-learning-6
-----
// 簡中資料
读论文《Natural Language Processing from Scratch》 - 知乎
https://zhuanlan.zhihu.com/p/59744800
Wednesday, July 15, 2020
全方位 AI 課程（精華篇）
全方位 AI 課程（精華篇）
2020/01/01
-----
Fig. Start（圖片來源：Pixabay）。
-----
Outline
一、LeNet
二、LeNet Python Lab
三、NIN
四、ResNet
五、FCN
六、YOLOv1
七、LSTM
八、Seq2seq
九、Attention
一０、ConvS2S
一一、Transformer
一二、BERT
一三、Weight Decay
一四、Dropout
一五、Batch Normalization
一六、Layer Nirmalization
一七、Adam
一八、Lookahead
-----
// Amazon.com：《Python Programming An Introduction to Computer Science》第三版。 (9781590282755) John Zelle Books
-----
// Amazon.com：Advanced Engineering Mathematics, 10Th Ed, Isv (9788126554232) Erwin Kreyszig Books
-----
// Amazon.com：Discrete - Time Signal Processing (9789332535039) Oppenheim Schafer Books
-----
// History of Deep Learning
-----
// History of Deep Learning
-----
// Deep Learning Paper
-----
// Deep Learning Paper
-----
// Deep Learning Paper
-----
// Recent Advances in CNN
-----
-----
-----
◎ LeNet
-----
-----
-----
-----
-----
-----
// 奇異值分解 (SVD) _ 線代啟示錄
-----
// Activation function 到底怎麼影響模型？ - Dream Maker
-----
// Activation function 到底怎麼影響模型？ - Dream Maker
-----
-----
-----
-----
-----
-----
◎ NIN
-----
-----
-----
◎ SENet
-----
# SENet
-----
◎ ResNet
-----
// DNN tip
-----
# ResNet v1
-----
-----
# ResNet-D
-----
# ResNet v2
-----
# ResNet-E
-----
# ResNet-V
-----
◎ FCN
-----
# FCN
-----
# FCN
-----
-----
◎ YOLOv1
-----
# YOLO v1
-----
# YOLO v1
-----
# YOLO v1
-----
◎ YOLOv3
-----
// Sensors _ Free Full-Text _ Improved UAV Opium Poppy Detection Using an Updated YOLOv3 Model _ HTML
-----
◎ LSTM
-----
-----
-----
◎ Seq2seq
-----
-----
◎ Attention
-----
-----
// Attention and Memory in Deep Learning and NLP – WildML
-----
◎ ConvS2S
-----
-----
-----
◎ Transformer
-----
// Attention Attention!
-----
-----
-----
-----
-----
-----
◎ BERT
-----
# BERT
-----
GPT-1
-----
// LeeMeng - 直觀理解 GPT-2 語言模型並生成金庸武俠小說
-----
# GPT-1
-----
ELMo
-----
// Learn how to build powerful contextual word embeddings with ELMo
-----
BERT
-----
// LeeMeng - 進擊的 BERT：NLP 界的巨人之力與遷移學習
-----
// LeeMeng - 進擊的 BERT：NLP 界的巨人之力與遷移學習
-----
// LeeMeng - 進擊的 BERT：NLP 界的巨人之力與遷移學習
-----
◎ Weight Decay
-----
// DNN tip
-----
-----
◎ Dropout
-----
// Dropout, DropConnect, and Maxout Mechanism Network. _ Download Scientific Diagram
-----
◎ Batch Normalization
-----
# PN
-----
// [ML筆記] Batch Normalization
-----
// An Intuitive Explanation of Why Batch Normalization Really Works (Normalization in Deep Learning Part 1) _ Machine Learning Explained
-----
# BN
-----
◎ Layer Normalization
-----
// 你是怎样看待刚刚出炉的 Layer Normalisation 的？ - 知乎
-----
// Weight Normalization and Layer Normalization Explained (Normalization in Deep Learning Part 2) _ Machine Learning Explained
-----
◎ Adam
-----
// SGD算法比较 – Slinuxer
-----
◎ Lookahead
-----
// Lookahead Optimizer k steps forward, 1 step back - YouTube
-----
-----
-----
References
AI 三部曲（深度學習：從入門到精通）
https://hemingwang.blogspot.com/2019/05/trilogy.html
-----
Amazon.com：《Python Programming An Introduction to Computer Science》第三版。 (9781590282755) John Zelle Books
https://www.amazon.com/-/zh_TW/dp/1590282752/
Amazon.com：Advanced Engineering Mathematics, 10Th Ed, Isv (9788126554232) Erwin Kreyszig Books
https://www.amazon.com/-/zh_TW/dp/8126554231/
Amazon.com：Discrete - Time Signal Processing (9789332535039) Oppenheim Schafer Books
https://www.amazon.com/-/zh_TW/dp/9332535035/
-----
History of Deep Learning
Deep Learning Paper
Recent Advances in CNN
-----
奇異值分解 (SVD) _ 線代啟示錄
https://ccjou.wordpress.com/2009/09/01/%E5%A5%87%E7%95%B0%E5%80%BC%E5%88%86%E8%A7%A3-svd/
Activation function 到底怎麼影響模型？ - Dream Maker
https://yuehhua.github.io/2018/07/27/activation-function/
DNN tip
http://speech.ee.ntu.edu.tw/~tlkagk/courses/ML_2016/Lecture/DNN%20tip.pdf
Sensors _ Free Full-Text _ Improved UAV Opium Poppy Detection Using an Updated YOLOv3 Model _ HTML
https://www.mdpi.com/1424-8220/19/22/4851/htm
Attention and Memory in Deep Learning and NLP – WildML
http://www.wildml.com/2016/01/attention-and-memory-in-deep-learning-and-nlp/
Attention Attention!
https://lilianweng.github.io/lil-log/2018/06/24/attention-attention.html
[ML筆記] Batch Normalization
http://violin-tao.blogspot.com/2018/02/ml-batch-normalization.html
An Intuitive Explanation of Why Batch Normalization Really Works (Normalization in Deep Learning Part 1) _ Machine Learning Explained
https://mlexplained.com/2018/01/10/an-intuitive-explanation-of-why-batch-normalization-really-works-normalization-in-deep-learning-part-1/
你是怎样看待刚刚出炉的 Layer Normalisation 的？ - 知乎
https://www.zhihu.com/question/48820040
Weight Normalization and Layer Normalization Explained (Normalization in Deep Learning Part 2) _ Machine Learning Explained
https://mlexplained.com/2018/01/13/weight-normalization-and-layer-normalization-explained-normalization-in-deep-learning-part-2/
-----
全方位 AI 課程（六十小時搞定深度學習）
http://hemingwang.blogspot.com/2020/01/all-round-ai-lectures.html
全方位 AI 課程報名處
https://www.facebook.com/permalink.php?story_fbid=113391586856343&id=104808127714689
2020/01/01
-----
Fig. Start（圖片來源：Pixabay）。
-----
Outline
一、LeNet
二、LeNet Python Lab
三、NIN
四、ResNet
五、FCN
六、YOLOv1
七、LSTM
八、Seq2seq
九、Attention
一０、ConvS2S
一一、Transformer
一二、BERT
一三、Weight Decay
一四、Dropout
一五、Batch Normalization
一六、Layer Nirmalization
一七、Adam
一八、Lookahead
-----
// Amazon.com：《Python Programming An Introduction to Computer Science》第三版。 (9781590282755) John Zelle Books
-----
// Amazon.com：Advanced Engineering Mathematics, 10Th Ed, Isv (9788126554232) Erwin Kreyszig Books
-----
// Amazon.com：Discrete - Time Signal Processing (9789332535039) Oppenheim Schafer Books
-----
// History of Deep Learning
-----
// History of Deep Learning
-----
// Deep Learning Paper
-----
// Deep Learning Paper
-----
// Deep Learning Paper
-----
// Recent Advances in CNN
-----
-----
-----
◎ LeNet
-----
-----
-----
-----
-----
-----
// 奇異值分解 (SVD) _ 線代啟示錄
-----
// Activation function 到底怎麼影響模型？ - Dream Maker
-----
// Activation function 到底怎麼影響模型？ - Dream Maker
-----
-----
-----
-----
-----
-----
◎ NIN
-----
-----
-----
◎ SENet
-----
# SENet
-----
◎ ResNet
-----
// DNN tip
-----
# ResNet v1
-----
-----
# ResNet-D
-----
# ResNet v2
-----
# ResNet-E
-----
# ResNet-V
-----
◎ FCN
-----
# FCN
-----
# FCN
-----
-----
◎ YOLOv1
-----
# YOLO v1
-----
# YOLO v1
-----
# YOLO v1
-----
◎ YOLOv3
-----
// Sensors _ Free Full-Text _ Improved UAV Opium Poppy Detection Using an Updated YOLOv3 Model _ HTML
-----
◎ LSTM
-----
-----
-----
◎ Seq2seq
-----
-----
◎ Attention
-----
-----
// Attention and Memory in Deep Learning and NLP – WildML
-----
◎ ConvS2S
-----
-----
-----
◎ Transformer
-----
// Attention Attention!
-----
-----
-----
-----
-----
-----
◎ BERT
-----
# BERT
-----
GPT-1
-----
// LeeMeng - 直觀理解 GPT-2 語言模型並生成金庸武俠小說
-----
# GPT-1
-----
ELMo
-----
// Learn how to build powerful contextual word embeddings with ELMo
-----
BERT
-----
// LeeMeng - 進擊的 BERT：NLP 界的巨人之力與遷移學習
-----
// LeeMeng - 進擊的 BERT：NLP 界的巨人之力與遷移學習
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// LeeMeng - 進擊的 BERT：NLP 界的巨人之力與遷移學習
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◎ Weight Decay
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// DNN tip
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# AdamW
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◎ Dropout
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// Dropout, DropConnect, and Maxout Mechanism Network. _ Download Scientific Diagram
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◎ Batch Normalization
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# PN
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// [ML筆記] Batch Normalization
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// An Intuitive Explanation of Why Batch Normalization Really Works (Normalization in Deep Learning Part 1) _ Machine Learning Explained
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# BN
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◎ Layer Normalization
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// 你是怎样看待刚刚出炉的 Layer Normalisation 的？ - 知乎
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// Weight Normalization and Layer Normalization Explained (Normalization in Deep Learning Part 2) _ Machine Learning Explained
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◎ Adam
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// SGD算法比较 – Slinuxer
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◎ Lookahead
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// Lookahead Optimizer k steps forward, 1 step back - YouTube
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References
AI 三部曲（深度學習：從入門到精通）
https://hemingwang.blogspot.com/2019/05/trilogy.html
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Amazon.com：《Python Programming An Introduction to Computer Science》第三版。 (9781590282755) John Zelle Books
https://www.amazon.com/-/zh_TW/dp/1590282752/
Amazon.com：Advanced Engineering Mathematics, 10Th Ed, Isv (9788126554232) Erwin Kreyszig Books
https://www.amazon.com/-/zh_TW/dp/8126554231/
Amazon.com：Discrete - Time Signal Processing (9789332535039) Oppenheim Schafer Books
https://www.amazon.com/-/zh_TW/dp/9332535035/
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History of Deep Learning
Alom, Md Zahangir, et al. "The history began from alexnet: A comprehensive survey on deep learning approaches." arXiv preprint arXiv:1803.01164 (2018).
https://arxiv.org/ftp/arxiv/papers/1803/1803.01164.pdf Deep Learning Paper
LeCun, Yann, Yoshua Bengio, and Geoffrey Hinton. "Deep learning." nature 521.7553 (2015): 436.
https://creativecoding.soe.ucsc.edu/courses/cs523/slides/week3/DeepLearning_LeCun.pdf Recent Advances in CNN
Gu, Jiuxiang, et al. "Recent advances in convolutional neural networks." Pattern Recognition 77 (2018): 354-377.
https://arxiv.org/pdf/1512.07108.pdf-----
奇異值分解 (SVD) _ 線代啟示錄
https://ccjou.wordpress.com/2009/09/01/%E5%A5%87%E7%95%B0%E5%80%BC%E5%88%86%E8%A7%A3-svd/
Activation function 到底怎麼影響模型？ - Dream Maker
https://yuehhua.github.io/2018/07/27/activation-function/
DNN tip
http://speech.ee.ntu.edu.tw/~tlkagk/courses/ML_2016/Lecture/DNN%20tip.pdf
Sensors _ Free Full-Text _ Improved UAV Opium Poppy Detection Using an Updated YOLOv3 Model _ HTML
https://www.mdpi.com/1424-8220/19/22/4851/htm
Attention and Memory in Deep Learning and NLP – WildML
http://www.wildml.com/2016/01/attention-and-memory-in-deep-learning-and-nlp/
Attention Attention!
https://lilianweng.github.io/lil-log/2018/06/24/attention-attention.html
[ML筆記] Batch Normalization
http://violin-tao.blogspot.com/2018/02/ml-batch-normalization.html
An Intuitive Explanation of Why Batch Normalization Really Works (Normalization in Deep Learning Part 1) _ Machine Learning Explained
https://mlexplained.com/2018/01/10/an-intuitive-explanation-of-why-batch-normalization-really-works-normalization-in-deep-learning-part-1/
你是怎样看待刚刚出炉的 Layer Normalisation 的？ - 知乎
https://www.zhihu.com/question/48820040
Weight Normalization and Layer Normalization Explained (Normalization in Deep Learning Part 2) _ Machine Learning Explained
https://mlexplained.com/2018/01/13/weight-normalization-and-layer-normalization-explained-normalization-in-deep-learning-part-2/
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全方位 AI 課程（六十小時搞定深度學習）
http://hemingwang.blogspot.com/2020/01/all-round-ai-lectures.html
全方位 AI 課程報名處
https://www.facebook.com/permalink.php?story_fbid=113391586856343&id=104808127714689