about-sim

Stanford dl4nlp lecture note

• Lecture note 1
• Lecture note 2
• Lecture note 3
• Lecture note 4
• Lecture note 5

Machine learning Basic

• Note for Backpropagation
• 세상의 (거의) 모든 머신러닝 문제 공략법
• 쉽게쓰여진 MCMC
• Optimization: Stochastic Gradient Descent] [note]
• BackPropagation Through Time

word2vec

• 딥러닝, NLP, 표현(Deep Learning, NLP, and Representations)
• woer2vec explained
• word2vec Parameter Learning Explained [note]
• Query2Vec: Learning Deep Intentions from Heterogenous Search Logs
• Search Retargeting using Directed Query Embeddings
• Distributed Representations of Sentences and Documents
• GloVe: Global Vectors for Word Representation
• Improving Word Representations via Global Context and Multiple Word Prototypes
• Bag of Tricks for Efficient Text Classification pdf note

Deep Neural Networks

• Deep Neural Networks for YouTube Recommendations [note] [요약]

Convolutional neural networks

• 콘볼루션 넷: 모듈 관점 (Conv Nets: A Modular Perspective)
• IMPLEMENTING A CNN FOR TEXT CLASSIFICATION IN TENSORFLOW (한글 번역)
• 자연어 처리 문제를 해결하는 CONVOLUTIONAL NEURAL NETWORKS 이해하기
• CS231n: Convolutional Neural Networks for Visual Recognition
• CONNECTING IMAGES AND NATURAL LANGUAGE

Recurrent neural networks

• Recurrent Neural Network (RNN) Tutorial - Part 1
• RNN Tutorial Part 2 - Python, NumPy와 Theano로 RNN 구현하기[note]
• RNN Tutorial Part 3 - BPTT와 Vanishing Gradient 문제
• • RNN Tutorial Part 4 - GRU/LSTM RNN 구조를 Python과 Theano를 이용하여 구현하기
• Recurrent neural network based language model
• EXTENSIONS OF RECURRENT NEURAL NETWORK LANGUAGE MODEL
• The Unreasonable Effectiveness of Recurrent Neural Networks
• 한글번역
• RNNS IN TENSORFLOW, A PRACTICAL GUIDE AND UNDOCUMENTED FEATURES
• Understanding LSTM Networks
  • 한글번역 http://www.whydsp.org/280

Restricted Boltzmann Machines

• 제한 볼츠만 머신 초보자 튜토리얼
• RBM 이해하기
• 딥 오토인코더
• Autoencoder vs RBM (+ vs CNN)

Vector search

• An Investigation of Practical Approximate Nearest Neighbor Algorithms

deeplearning4j

• Deeplearning4j 소개
• Deeplearning4j 퀵스타트 가이드
• 아이겐벡터, 공분산, 주성분분석(PCA), 엔트로피의 기초
• 심층 신경망 (딥 뉴럴넷) 소개
• 컨볼루션 신경망(뉴럴 네트워크)
• LSTM 자세한 튜토리알!
• Deeplearning4j의 RNN 모델 사용방법
• 자연어처리 : word2vec
• 제한 볼츠만 머신 초보자 메뉴얼
• 딥 오토인코더

tensorflow

• Large-Scale Machine Learning on Heterogeneous Distributed Systems
• https://github.com/aymericdamien/TensorFlow-Examples
• Tensorflow for machine intelligence

distributed system

• Large Scale Distributed Deep Networks