├── README.md ├── Session#1 ├── Data-sciencist-at-SF-Bay-area.pdf └── Session#1.md └── session8_Text_Practice.ipynb /README.md: -------------------------------------------------------------------------------- 1 | # Machine Learning Study Group: Deep Learning with Python 2 | 3 | ## 目的: 4 | 協助想要往 Data Science 領域發展的 Women Who Code 成員學習 Deep Learning。 5 | 6 | ## 方法: 7 | 成立 Machine Learning Study Group。透過導讀、實作和討論，讓 members 共同來學習。 8 | 9 | ## Deep Learning with Python 讀書會 10 | + Machine Learning Study Group 11 | + 系列活動，為期十次 12 | + 採用台北與加州灣區連線方式舉行 13 | + 跨國志工導讀、實作及討論 14 | + 什麼是讀書會 15 | + 參考 : [認識HPX讀書會][1] 16 | + 讀書會屬於大家，是大家相互學習的形式，並非教學。 17 | + 讀書會成員認領導讀 (非強迫性) 18 | + 每章節獨立，歡迎新成員加入 19 | + 本次用書: [Deep Learning with Python][2] 20 | + [Github: fchollet/deep-learning-with-python-notebooks][13] 21 | + 請自行準備 22 | + Chapter in the book: 23 | + [進度 台北時間 灣區時間] 24 | - [x] [第一週][9] 9/15 9/14 25 | + **導讀** 第一章 [What is deep learning][10] 26 | - Milla Shih 27 | + **實作** 主題 [在 Google Colab 使用 Keras][11] 28 | + Sidney Lin 29 | + **分享** 主題 [Fast Track your Career in Data Science][12] 30 | + Chu-Cheng Hsieh 31 | - [x] 第二週 9/22 9/21 32 | + **導讀** 第二章 [Before we begin: the mathematical building blocks of neural networks][14] 33 | + Sidney Lin 34 | - [x] 第三週 9/29 9/28 35 | + **導讀** 第三章 [Getting started with neural networks][17] 36 | + Katy Chou 37 | + **補充** [But what *is* a Neural Network? | Deep learning, chapter 1][18] 38 | + Gomax 39 | + **補充** [How Deep Learning Neural Network Works][19] 40 | + Roger 41 | - [x] 第四週 10/13 10/12 42 | + **導讀** 第四章 [Fundamentals of machine learning][20] 43 | + Noah Chen 44 | - [x] 第五週 10/20 10/19 45 | + **導讀** 第五章 [Deep learning for computer vision][21] 46 | + 曾韋霖 47 | - [x] 第六週 10/27 10/26 48 | + **實作** 第五章 [實作][22] 49 | + 曾韋霖、Enzo 50 | + **分享** 主題 [import AI*][23] 51 | + 王品淳 52 | - [x] 第七週 11/3 11/2 53 | + **導讀** 第六章 [Deep learning for text and sequences][24] 54 | + Hsin-Wei Tsao, Alicia Yi-Ting Tsai 55 | + **補充** [最後Hsin-Wei分享的display_closestwords_tsnescatterplot.ipynb][25] 56 | + Hsin-Wei Tsao 57 | - [x] 第八週 11/10 11/9 58 | + **實作** 第六章 [Deep learning for text and sequences Practice][27] 59 | + **實作** 第六章 [實作jupyternotebook][26] 60 | + Hsin-Wei Tsao, Alicia Yi-Ting Tsai 61 | - [x] 第九週 11/17 11/16 62 | + **導讀** 第七章 [Advanced deep-learning best practices][28] 63 | + Yu-Hsuan Chen 64 | - [x] 第十週 12/9 12/8 65 | + **導讀** 第七章 [Advanced deep-learning best practices][28] 66 | + Yu-Hsuan Chen 67 | - [x] 第十一週 12/16 12/15 68 | + **導讀** 第八章 [Generative deep learning][29] 69 | + Jay Tao 70 | + **導讀** 第九章 [Conclusions][30] 71 | + Jay Tao 72 | + **補充** [Singularity][31] 73 | + Ziad 74 | 75 | ## 課程時間與地點: 76 | + 台北: 77 | + 三創 11 F 78 | + Start time: 9:40 79 | + 灣區: 80 | + Santa Clara University Library Room 133 (500 El Camino Real, Santa Clara) 81 | + Start time: 18:40 82 | 83 | ## 資訊與工具 84 | + 資訊發布以 Facebook 和 Meetup 為優先 85 | + [台北Meetup][Women Who Code Taipei][3] 86 | + [灣區活動頁][Machine Learning Study Group : Deep Learning with Python][8] 87 | + [FB粉絲頁][Women Who Code Taipei][4] 88 | + [FB社團][Women Who Code Taipei][5] 89 | + [FB社團][Girls in Tech-Taiwan/Taipei Women in Tech][6] 90 | + [FB社團][Data Science Meetup 台灣資料科學社群][7] 91 | + 提問討論有2種方式 92 | + Github 的 [Issue][15] 93 | + [Slack][16] 94 | 95 | ## 學習資源 96 | + **womenwhocode**[womenwhocode的學習資源][49] 97 | + **台大** [李宏毅老師的youtube頻道][59] 98 | + **台大** [林軒田老師的機器學習基石(上)-數學基礎][62] 99 | + **台大** [林軒田老師的機器學習基石(下)-演算法基礎][63] 100 | + **政大**[成為python數據分析達人的第一課][50] 101 | + Enzo 推薦 102 | + **Udemy**[机器学习 A-Z (Machine Learning A-Z in Chinese)][51] 103 | + Enzo 推薦 104 | + **Fb粉絲頁** [ccClub][54] & Medium:[Coding & Co-working Club][53] 105 | + **Google** [Google機器學習資源1:Prerequisites and Prework][56] 106 | + **Google** [Google機器學習資源2:Machine Learning Crash Course][57] 107 | + **Google** [Google機器學習資源3:Path of Machine Learning][58] 108 | + **Microsoft** [AI School: ML Crash Course][60] 109 | + **Udacity** [deep-learning-v2-pytorch][61] 110 | + **Coursera** [吳恩達老師的 Deep Learning系列課程][64] 111 | + **書籍** [練好機器學習的基本功][55] 112 | 113 | 114 | 115 | 116 | 117 | 118 | 119 | 120 | 121 | [1]:https://hpx.tw/archives/18982 122 | [2]:https://www.manning.com/books/deep-learning-with-python 123 | [3]:https://www.meetup.com/Women-Who-Code-Taipei/ 124 | [4]:https://www.facebook.com/wwcodetaipei/ 125 | [5]:https://www.facebook.com/groups/wwcodetaipei/?ref=group_header 126 | [6]:https://www.facebook.com/groups/420817431404071/?ref=group_header 127 | [7]:https://www.facebook.com/groups/datasciencemeetup/?ref=group_header 128 | [8]:https://www.facebook.com/events/1901939603261051/ 129 | [9]:https://github.com/WomenWhoCodeTaipei/DeepLearningwithPython/tree/master/Session%231 130 | [10]:https://ppt.cc/fflBlx 131 | [11]:https://lihi.cc/iaAoO 132 | [12]:https://github.com/WomenWhoCodeTaipei/DeepLearningwithPython/blob/master/Session%231/Data-sciencist-at-SF-Bay-area.pdf 133 | [13]:https://github.com/fchollet/deep-learning-with-python-notebooks 134 | [14]:https://lihi.cc/UUnLP 135 | [15]:https://github.com/WomenWhoCodeTaipei/DeepLearningwithPython/issues/1 136 | [16]:https://goo.gl/forms/7hFI7tEf6Z4exCT82 137 | [17]:https://lihi.cc/eaHoT 138 | [18]:https://youtu.be/aircAruvnKk 139 | [19]:https://www.youtube.com/watch?v=ILsA4nyG7I0&feature=youtu.be&t=852 140 | [20]:http://bit.ly/deep_learning_with_python_ch4 141 | [21]:https://drive.google.com/file/d/1oZsvDgy73Gd4jjG9UqwE2kwWhgjjebNv/view?fbclid=IwAR2AqvFtM_Q5dUDJmz9J6Q2kqGUTUHAVah84NLcB-jbhl_LCf7atkfV8jlQ 142 | [22]:https://docs.google.com/presentation/d/1x44qt4YOyIbAL-TvQHClA2QU87BiuN0wSLNtJgUEYKQ/edit?fbclid=IwAR382IpEmEfxg1KK7wwmv6qK4BF1Q4J7vrWBlEwCaoTwocrP1ds_rVb1Td0#slide=id.g35f391192_00 143 | [23]:https://docs.google.com/presentation/d/1uf7j-Fs0OD2gfqzJC35prFoHozv_9IBWV5azjcuLjqE/edit?fbclid=IwAR2yfW0C4m7PL8-7F1AWNCCZsEdp8rnNLRO4ETSvFimTGYavecqyCXcrMHk#slide=id.g44ca355d22_0_0 144 | [24]:https://docs.google.com/presentation/d/1-b9TFwkdiVLC3WdV1uAaXQP1d2I9dRJM8zfNx6uwEIE/edit?fbclid=IwAR1NYM_7OK7iROxFoJ_AfR_1d3Rvrh5vxhZ99_XRBRUQmRObbX3CUgtzd_g#slide=id.g456bf0dcf7_6_431 145 | [25]:https://l.facebook.com/l.php?u=https%3A%2F%2Fgist.github.com%2Faneesha%2Fda9216fb8d84245f7af6edaa14f4efa9%3Ffbclid%3DIwAR3X7BhnZZ2v3h_gIlFiajReJlutDcWS_n3e-p9MQqtufc1bUnCBoplJCnQ%23file-display_closestwords_tsnescatterplot-ipynb&h=AT1iOcQqYCJfrWmklJyraOG8e-3Vt2wjMNhOjfs5VdiKqx3CTfqnOsDsZAREBWZdqUhGExoP2T9x4Bgo7O59j6-vJJvq7BVQi225WrzDym02O04ZKquUZQjodPUT_LbhkXLMO-Xf 146 | [26]:https://github.com/WomenWhoCodeTaipei/DeepLearningwithPython/blob/master/session8_Text_Practice.ipynb 147 | [27]:https://docs.google.com/presentation/d/17EImL6qEwrJRz30315POVEPHi7mcnVhTOi4QwiSuST8/edit?fbclid=IwAR1MCdSX58RK9UOl5zSh5rfJ4Cxnh6_QOFy0VovBM6hqa6DEX4MKhf8tVSI#slide=id.p 148 | [28]:https://docs.google.com/presentation/d/1ukpQ_zBVqMQz1RosLuPbCLkrOqD5O_oQpV4u8wlo6Cc/edit?fbclid=IwAR2A8mBTAyup7j8Qb1PqvS6IC4Y_nRks0kRjQ57rdBcHz6dXcBns6OnqBTw#slide=id.g35f391192_00 149 | [29]:https://docs.google.com/presentation/d/1eukZLgAZTpLZSi-R-GfTOop1dEOykgf8kuQg5Mn1u50/edit?fbclid=IwAR2ahorQfwtpNLlrMs0JhVKDTkAQt8_hNkdAqL6ntFO3Dy0mQHIwy8iUN50#slide=id.g46410a78bf_0_0 150 | [30]:https://docs.google.com/presentation/d/1uBFRrLoyh1C1drMpd3KcNj9JqDbZZHK91TGbvzPHylI/edit?fbclid=IwAR2EHyOVqrU5UGTspjfPR29ki5VGXiM4M9E351FycpA2f03YQwpqUJ2xUhM#slide=id.g4a3f5b514e_0_0 151 | [31]:https://drive.google.com/drive/folders/1CDdgA4L5qxwEDOmdiqB7_aiVUTE6yLmI?usp=sharing 152 | 153 | [49]:https://www.womenwhocode.com/resources 154 | [50]:http://moocs.nccu.edu.tw/course/123/section/lecture 155 | [51]:https://www.udemy.com/machinelearningchinese/ 156 | [52]:http://moocs.nccu.edu.tw/course/132/section/lecture 157 | [53]:https://medium.com/ccclub 158 | [54]:https://www.facebook.com/ccclub.io/?__xts__%5B0%5D=68.ARCnhjk8stSyaFt_vriAHC14KT_e9rrZyhmEmIeymdpbi1DLM-wgJVITp3zXb9dRjT6aK95i-mgLRi8bG-ezFy7hunCpy-ZGYC0GkJEPvTmfjm5yOXlYXO7_0tUsMCv-h3SUlOdVvc63dyU8T7HpL2tktySLN0dLGl1AjfR0o4ZRyvplknijGkEYuWVqyacA4FkOfpqO2jBUxnC4psEQp4Vp1lI-F621xi71ssw 159 | [55]:https://www.books.com.tw/products/0010797283 160 | [56]:https://developers.google.com/machine-learning/crash-course/prereqs-and-prework?fbclid=IwAR0UUErHm9a1BmT2X8MKoiV0P8eVdfIomiN-Oq7W-ZazWAMzwHsjMjbS0is 161 | [57]:https://developers.google.com/machine-learning/crash-course/?utm_source=DevRel&utm_medium=StudyJam&utm_campaign=q1y2018&utm_term&utm_content=mlcc&fbclid=IwAR2EypJlNex4cxn_uL8QwRbK2GVS2PNrRQGYWv9L54IQLqkx83QSs39xT_k 162 | [58]:https://techdevguide.withgoogle.com/paths/machine-learning/ 163 | [59]:https://www.youtube.com/channel/UC2ggjtuuWvxrHHHiaDH1dlQ/playlists 164 | [60]:https://aischool.microsoft.com/en-us/machine-learning/learning-paths/ml-crash-course 165 | [61]:https://github.com/udacity/deep-learning-v2-pytorch 166 | [62]:https://www.coursera.org/learn/ntumlone-mathematicalfoundations 167 | [63]:https://www.coursera.org/learn/ntumlone-algorithmicfoundations 168 | [64]:https://www.deeplearning.ai/ 169 | -------------------------------------------------------------------------------- /Session#1/Data-sciencist-at-SF-Bay-area.pdf: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/WomenWhoCodeTaipei/DeepLearningwithPython/44123a2d0ec17411989ef48266e57369afa4251f/Session#1/Data-sciencist-at-SF-Bay-area.pdf -------------------------------------------------------------------------------- /Session#1/Session#1.md: -------------------------------------------------------------------------------- 1 | 2 | # Chapter 1 - What is Deep Learning 3 | 4 | - 導讀志工: Milla shih 5 | - [What is Deep Learning][1] 6 | 7 | # 環境介紹 Colab 8 | 9 | - 導讀志工: Sidney Lin 10 | - [在Google Colab使用Keras][2] 11 | - 補充:[Colab的官方介紹][5] 12 | 13 | # 分享主題: Fast Track your Career in Data Science 14 | 15 | - 分享人: [Chu-Cheng Hsieh][3] 16 | - [Data-sciencist-at-SF-Bay-area.pdf][4] 17 | 18 | 19 | 20 | 21 | 22 | 23 | 24 | 25 | 26 | 27 | 28 | [1]:https://ppt.cc/fflBlx 29 | [2]:https://lihi.cc/iaAoO 30 | [3]:https://www.linkedin.com/in/chucheng/ 31 | [4]:https://github.com/WomenWhoCodeTaipei/DeepLearningwithPython/blob/master/Session%231/Data-sciencist-at-SF-Bay-area.pdf 32 | [5]:https://colab.research.google.com/notebooks/welcome.ipynb 33 | --------------------------------------------------------------------------------