안녕하세요. 2017 인공지능 B팀 여러분!
7월 15일 10주차 스터디는 9주차 스터디 장소와 같은 곳에서 진행 할 예정입니다.
지난 스터디에 참석하지 못했으나 스터디에 참석을 희망하시는 분들은 아래에 댓글로
남겨 주시기 바랍니다.
장소 및 스터디 관련 의견사항이 있을 경우 댓글로 남겨주시면 감사하겠습니다.
- 시즌 1 - 딥러닝의 기본 (TF 1.0 lab 업데이트중) 비디오 리스트
-- [ lec11-2: ConvNet Max pooling 과 Full Network ] 부터
일시:
- 7월 15일(토요일)
- 오전 9시 ~ 오후 1시
추천도서:
|
『 밑바닥부터 시작하는 딥러닝 』(한빛미디어, 2017) | GitHub |
관련 포스트 & 논문:
- Convolutional neural networks, Part 1(post) | The Morning Paper
-- Convolutional neural networks, Part 2(post) | The Morning Paper
-- Convolutional neural networks, Part 3(post) | The Morning Paper
- Recurrent Neural Network models(post) | The Morning Paper
기타:
- Convolutional Networks | Deep Learning Summer School, Montreal 2015
- 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
- Machine Learning | Coursera - Andrew Ng
-- Machine Learning(CS229) | YouTube — Andrew Ng, Stanford University [FULL COURSE]
-- Machine Learning(Coursera Contents) | YouTube — Andrew Ng, Stanford University
-- CS 229 Machine Learning Course Materials
- 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
- Learn TensorFlow and deep learning, without a Ph.D.
-- TensorFlow and Deep Learning without a PhD, Part 1 (Google Cloud Next '17)
-- TensorFlow and Deep Learning without a PhD, Part 2 (Google Cloud Next '17)
- Deep Learning Book Review | YouTube
-- 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)
-- Deep Learning_An MIT Press book - Ian Goodfellow and Yoshua Bengio and Aaron Courville
--- Chapter 9 : Convolutional Networks
--- Chapter 10 : Sequence Modeling: Recurrent and Recursive Nets
-- tensorflow/tensorflow/examples/tutorials/mnist/
- TensorFlow Machine Learning Cookbook_A Packt Publishing Book | GitHub
-- Ch 8: Convolutional Neural Networks | GitHub
-- Ch 9: Recurrent Neural Networks | GitHub
- TensorFlow Tutorial - used by Nvidia | GitHub
-- Lab2 - CNN | GitHub
-- Lab3 - RNN | GitHub
- 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
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