Deep Learning 101, Taiwan’s pioneering and highest deep learning meetup, launched on 2016/11/11 @ 83F, Taipei 101

AI是一條孤獨且充滿惶恐及未知的旅程,花俏絢麗的收費課程或活動絕非通往成功的捷徑。
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TonTon Huang Ph.D. 發起,及其當時任職公司(台灣雪豹科技)無償贊助場地及茶水點心。

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Deep Learning 101 Meetup



Deep Learning 101 Meetup 歷年活動 (摘要逐字稿及語音皆由 Gemini 2.5 Pro Preview 05-06 及 NotebookLM 所生成,處理好會陸續補上)

No. 主題 (網頁) 日期 (YT) 講者 (摘要) 語音
49 On the Relationship among Convolution Attention and GNN 2022/05/06 杜岳華
48 Model-Based Reinforcement Learning 2021/07/16 翁崇恒
47 深度學習也可以學傅立葉轉換 2020/12/04 杜岳華
45 Modeling the Dynamics of SGD by Stochastic Differential Equation 2020/09/11 Mark Chang
44 神經網路的黑執事 2020/08/21 Mark Liou
43 幾何深度學習是在幾何什麼的? 2020/07/24 杜岳華
42 information in the weights 2020/06/19 Mark Chang
41 NLP Landing & Machine Reading Comprehension 2020/05/29 Ian & Hsiang
40 Instance Segmentation 2020/05/01 顏志翰 (Bean)
39 高維資料的降維演算法及視覺化 2020/03/20 杜岳華
38 PAC Bayesian for Deep Learning 2020/02/14 Mark Chang
37 Introduction to geometric deep learning with implementation 2020/01/10 杜岳華
36 Explainable Artificial Intelligence 2019/12/13 何宗諭 (Jiero)
34 High-Dimensional Continuous Control Using Generalized Advantage Estimation 2019/10/04 Cecile Liu
33 Hardware Accelerators for Machine Learning 2019/08/23 林家銘
32 Transfer Learnings & Multitask Learning 2019/07/19 Mark Chang
31 Machine Teaching 2019/06/28 Mark Liou
30 The Hackathon/Formosa Grand Challenge Between Us 2019/05/17 Ryan Chao
29 Domain adaptation 2019/03/08 Mark Chang
28 Deep knowledge representation and reasoning 2019/02/15 Chin-Hui Chen
27 Semi-Supervised Classification with Graph Convolutional Networks 2019/01/11 Bean Yen
26 Machine Reading Comprehension 2018/12/07 Nat, Alice & Ian
24 SOC: Social-network Opinion and Comment 2018/10/12 Nat Lee
23 Recommender System 2018/09/14 SAS
22 Deep Bilateral Learning for Real-Time Image Enhancement 2018/08/17 Ken Huang
21 Dynamic Routing Between Capsules 2018/07/06 Jiero Ho
20 VAE: A generative model for 2D anime character faces 2018/06/08 Nat, Boris, Alice, Ian
19 Towards Principled Methods for Training Generative Adversarial Networks 2018/05/11 Mark Chang
18 Deep Generative Models @ Deep Learning Book Chapter 20 2018/04/13 文字摘要
17 Approximate Inference @ Deep Learning Book Chapter 19 2018/03/16 文字摘要
15 Confronting the Partition Function @ Deep Learning Book Chapter 18 2018/01/12 何宗諭 (Jiero)
14 Monte Carlo Methods @ Deep Learning Book Chapter 17 2017/12/15 Ian Wang
12 Structured Probabilistic Models @ Deep Learning Book Chapter 16 2017/10/27 文字摘要
11 Autoencoders @ Deep Learning Book Chapter 14 2017/09/08 Nat Lee
10 Linear Factor Models @ Deep Learning Book Chapter 13 2017/08/11 文字摘要
09 Representation Learning @ Deep Learning Book Chapter 15 2017/07/07 文字摘要
Applications @ Deep Learning Book Chapter 12      
Practical Methodology @ Deep Learning Book Chapter 11      
07 Recurrent and Recursive Nets @ Deep Learning Book Chapter 10 2017/05/05 文字摘要
06 Convolutional Networks @ Deep Learning Book Chapter 9 2017/04/14 文字摘要
05 Optimization for Training Deep Models @ Deep Learning Book Chapter 8 2017/03/10 文字摘要
04 Regularization for Deep Learning @ Deep Learning Book Chapter 7 2017/02/10 文字摘要
03 Deep Feedforward Networks @ Deep Learning Book Chapter 6