Deeplunch팀의 Kaggle Data Science Bowl 도전기(1) – 케글 도전 팁

Deeplunch팀의 Kaggle Data Science Bowl 도전기(1) – 케글 도전 팁   http://esuerid.blogspot.kr/2017/04/deeplunch-kaggle-data-science-bowl-1.html?m=1

머신러닝 모델 개발 삽질 경험기

http://bcho.tistory.com/m/1174 머신러닝 모델 개발 삽질 경험기  

인공지능을 위한 머신러닝 알고리즘

https://tacademy.sktechx.com/live/player/onlineLectureDetail.action?seq=103   인공지능을 위한 머신러닝 알고리즘 인공지능에 관심이 있는 사람들에게 머신러닝 알고리즘의 개념과 원리를 설명합니다. 특히 머신러닝과 딥러닝 분야의 개발자에게 쉽게 설명된 핵심 이론과 함께 적용사례별 간단한 알고리즘 등을 보여주고 구현방법을 소개합니다. 강의에서는 지도학습과 비지도학습의 머신러닝 알고리즘을 다루며, 지도학습 알고리즘으로는 linear/logistic regression, 서포트 벡터 머신, 의사결정 트리, 신경망, CNN, RNN을, 비지도학습 알고리즘으로는 K-MEANS, DBSCAN 등을 살펴봅니다.   인공지능배포용

learningtensorflow

http://learningtensorflow.com/

MIT 6.S094: DL for Self-Driving Cars

https://tensorflow.blog/2017/01/26/mit-6-s094-dl-for-self-driving-cars/

140 Machine Learning Formulas

http://www.datasciencecentral.com/m/blogpost?id=6448529%3ABlogPost%3A515463

What is variational autoencoder?

http://nolsigan.com/blog/what-is-variational-autoencoder/

TensorFlow implementation of Learning from Simulated and Unsupervised Images through Adversarial Training

TensorFlow implementation of Learning from Simulated and Unsupervised Images through Adversarial Training https://github.com/carpedm20/simulated-unsupervised-tensorflow

Generative Adversarial Networks

Generative Adversarial Networks GANs (generative adversarial networks) is a rapidly advancing area of Deep Learning invented…

The Great A.I. Awakening

The Great A.I. Awakening   http://www.albireo.net/threads/45878/