안녕하세요.  

11주차(7월 22일_토) 스터디 내용과 참여 인원이 하기와 같았음을 알려 드립니다.

11주차 스터디/동영상 내용과 관련하여 토의 사항이 있을 경우 댓글로 남겨 주시면 감사하겠습니다.

 - 학습진도: 

- 동영상 : 

-- lec12: NN의 꽃 RNN 이야기 ,

-- ML lab12-1: RNN - Basics ,

-- ML lab12-2: RNN - Hi Hello Training ,

-- ML lab12-3: Long Sequence RNN ,

-- ML lab12-4: Stacked RNN + Softmax Layer ,

-- ML lab12-5: Dynamic RNN ,

-- ML lab12-6: RNN with Time Series Data

- 참여인원: 총 5 명

- 관련 포스트 & 논문:

-- Building Your Own Neural Machine Translation System in TensorFlow, Wednesday, July 12, 2017

--- Neural Machine Translation (seq2seq) Tutorial

- 참고 웹사이트: 

- TensorFlow Tutorial | YouTube

-- TensorFlow Tutorials | GitHub 

-- TensorFlow Tutorial #02 Convolutional Neural Network | YouTube

-- TensorFlow Tutorial #02 Convolutional Neural Network | GitHub

-- TensorFlow Tutorial #03-B Layers API | YouTube

-- TensorFlow Tutorial #03-B Layers API | GitHub

-- TensorFlow Tutorial #05 - Ensemble Learning | YouTube

-- TensorFlow Tutorial #05 - Ensemble Learning | GitHub

- Machine Learning | Coursera -  Andrew Ng 

-- Lecture Notes | Coursera

-- CS 229 Machine Learning Course Materials

- CS231n: Convolutional Neural Networks for Visual Recognition(Winter 2016)

-- CS231n Winter 2016 | YouTube

--- CS231n Winter 2016: Lecture 5: Neural Networks Part 2

--- CS231n Winter 2016: Lecture 6: Neural Networks Part 3 / Intro to ConvNets

--- CS231n Winter 2016: Lecture 7: Convolutional Neural Networks

--- CS231n Winter 2016: Lecture 10: Recurrent Neural Networks, Image Captioning, LSTM

-- Schedule and Syllabus(Winter 2016)

- CS224n: Natural Language Processing with Deep Learning​

-- Lecture Collection | Natural Language Processing with Deep Learning (Winter 2017) | YouTube

--- Lecture 8: Recurrent Neural Networks and Language Models

--- Lecture 13: Convolutional Neural Networks

-- Schedule and Syllabus

- Deep Learning Book Review | YouTube

-- Online Discussion: Deep Learning Book Ch 3

-- Online Discussion: Deep Learning Book Ch 9 (Part 1)

-- Online Discussion: Deep Learning Book Ch 9 (Part 2)

-- Online Discussion: Deep Learning Book Ch 10 (Part 1)

-- Online Discussion: Deep Learning Book Ch 10 (Part 2)

-- DeepLearningBook 

-- Deep Learning_An MIT Press book - Ian Goodfellow and Yoshua Bengio and Aaron Courville

--- Chapter 3: Probability and Information Theory

--- Chapter 9 : Convolutional Networks

--- Chapter 10 : Sequence Modeling: Recurrent and Recursive Nets