안녕하세요.
8주차(7월 1일_토) 스터디 내용과 참여 인원이 하기와 같았음을 알려 드립니다.
8주차 스터디/동영상 내용과 관련하여 토의 사항이 있을 경우 댓글로 남겨 주시면 감사하겠습니다.
- 학습진도:
- 동영상 :
--- ML lab 09-2: Tensorboard (Neural Net for XOR) ,
--- lec10-1: Sigmoid 보다 ReLU가 더 좋아 ,
--- lec10-2: Weight 초기화 잘해보자 ,
--- lec10-3: Dropout 과 앙상블 ,
--- lec10-4: 레고처럼 넷트웍 모듈을 마음껏 쌓아 보자
- 슬라이드 :
-- Lab 9-2 Tensorboard for XOR NN
-- Lab 9-2-E (Tensorboard for MNIST )
-- Lab 9-3 (optional) NN Backpropagation
-- Lecture 10-1 ReLU: Better non-linearity
-- Lecture 10-2 Initialize weights in a smart way
-- Lecture 10-3 NN dropout and model ensemble
-- Lecture 10-4 NN LEGO Play
- 참여인원: 총 8 명
- 예제코드:
- 참고:
- TensorFlow Tutorial | YouTube
-- TensorFlow Tutorials | GitHub
-- TensorFlow Tutorial #05 - Ensemble Learning
- Machine Learning | Coursera - Andrew Ng
-- CS 229 Machine Learning Course Materials
- CS231n: Convolutional Neural Networks for Visual Recognition(Winter 2016)
-- CS231n Winter 2016 | YouTube
-- Schedule and Syllabus(Winter 2016)
- Neural Networks for Machine Learning | Coursera - Prof. Geoffrey Hinton on Coursera in 2013
-- Neural Networks for Machine Learning | YouTube - Prof. Geoffrey Hinton on Coursera in 2012
-- CSC321 Winter 2014 - Lecture notes
- CS 229 Machine Learning | Stanford - Andrew Ng
- First Contact with TensorFlow(원서_번역내용) | 텐서플로우 블로그 (Tensor ≈ Blog)
- CS 20SI: Tensorflow for Deep Learning Research
-- CS 20SI: Tensorflow for Deep Learning Research(YouTube)
- CS 229 Machine Learning Course Materials | Standford
-- Linear Algebra Review and Reference
-- Binary classification with +/-1 labels
-- Supervised Learning, Discriminative Algorithms
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