- 전체보기(16)
- cs224n(13)
- NLP(13)
- parsing(2)
- RNN(2)
- 1x1Convolution(1)
- word embedding(1)
- GloVe(1)
- NeuralNetwork(1)
- ComputationGraph(1)
- TreeRNNS(1)
- Backpropagation(1)
- Machine Translation(1)
- Highway block(1)
- Neural Networks(1)
- word2vec(1)
- sequence(1)
- Word Window Classification(1)
- linguistic structure(1)
- Introduction and Word Vector(1)
- TextCNN(1)
- LSTM(1)
- lecture8(1)
- Residual block(1)
- Perplexity(1)
- co-occurrence matrix(1)
- transformer(1)
- Multi-layer RNN(1)
- Neural Language Model(1)
- Matrix Calculus(1)
- Embeddings(1)
- Attention(1)
- Bidirectional RNN(1)
- Vanishing gradient(1)
- Sequence to sequence(1)
- GRU(1)
- dependency(1)
- self-attention(1)
- NLP Reseach(1)
- BPTT(1)
- Lecture 6(1)
- Gradient Clipping(1)
- N-Gram(1)
- ConvNets(1)
- CNN(1)
- VD-CNN(1)
- BatchNorm(1)
[CS224n] Lecture 18 - Constituency Parsing TreeRNNS
작성자 : 투빅스 13기 정민준 > Contents Constituency Parsing Simple TreeRNN Syntactically-United RNN Matrix-Vector RNN Recursive Neural Tensor Network 1.Consti
[CS224n] Lecture 15 - Natural Language Generation
작성자 : 투빅스 13기 김민정 > Contents Decoding Algorithm Neural Summarization Copy Mechanisms NLG Using Unpaired Corpus 1. Decoding Algorithm 시작하기 전에 NLG가 무
[CS224n] Lecture 14 - Transformer and Self-Attention
작성자 : 투빅스 13기 정주원 > Contents RNN, CNN, and Self-Attention Transformer Image Transformer Music Transformer 1. RNN, CNN, and Self-Attention 
[CS224n] Lecture 13 - Contextual Word Embeddings
작성자 : 투빅스 13기 오진석 > Contents Reflections on word representations Pre-ELMo and ELMo ULMfit and onward Transformer archietectures BERT CS224n의 13번째 강의
[CS224n] Lecture 12 - Subwords
작성자 : 투빅스 14기 장예은 > Contents Purely Character-Level Models Subword-Models Hybrid Models Cs224n 강의에서 언어학 관련 용어가 많이 등장하여 자주 등장하는 용어를 정리해보았습니다. 강의를 들으시
[CS224n] Lecture 11 - ConvNets for NLP
작성자 : 투빅스 13기 이예진 > Contents Intro 1d Convolution for Text CNN for Classification 추가 & 정리 Deep CNN for Text 1. Intro 기존 RNN의 문제와 CNN 기존 RNN계열의 모델은
[CS224n] Lecture10 - Question Answering
작성자 : 투빅스 13기 김미성 > Contents Motivation & History Standford Question Answering Dataset(SQuAD) QA model 1. Motivation & History 우리는 종종 질문에 대한 답을 원합니
[CS224n] Lecture 9 - Practical Tips for Final Projects
작성자 : 투빅스 14기 민거홍Lecture 9는 NLP 연구 전반과 CS224n 최종 프로젝트에 대해 다룹니다. 1\. Starting Research2\. Review of Gated Neural Sequence Models 3\. MT Topics4\. Rese
[CS224n] Lecture 8 - Machine Translation, Sequence-to-sequence and Attention
작성자 : 투빅스 14기 고경태 > Contents Machine Translation Sequence to sequence Neural technique: Attention 목차의 흐름은 전 목차 주제에서의 한계점을 극복하고 발전하는 방향으로 진행됩니다. 즉, 기계
[CS224n] Lecture 7 - Vanishing Gradients And Fancy RNNs
작성자 : 투빅스 13기 최혜빈 > Contents Vanishing gradient problem LSTM GRU More fancy RNN variants Vanishing gradient problem Remark) Backpropagation for RNNs
[CS224n] Lecture 6 - Language Models and Recurrent Neural Network
작성자 : 투빅스 13기 김민정 > Contents Language Modeling N-gram Language Model Neural Language Model RNN Language Model Perplexity 1. Language Modeling 많은 사람
[CS224n] Lecture 5 - Linguistic Structure: Dependency Parsing
작성자 : 투빅스 13기 오진석Syntactic Structure: Consitituency and DependencyDependency Grammar and TreebanksTransition-based dependency parsingNeural Denpendenc
[CS224n] Lecture 4 - Backpropagation and Computation Graph
작성자 : 투빅스 13기 이재빈 > Contents Matrix Gradients for Neural Nets Computation Graphs and Backpropagation Tips and Tricks for Neural Networks 1. Matrix G
[CS224n] Lecture 3 - Word Window Classification, Neural Networks, and Matrix Calculus
작성자 : 투빅스 14기 고경태 > Contents Classification review/introduction Neural Networks introduction Neural Networks in NLP! Matrix calculus! 1. Classificati
[CS224n] Lecture 2 - Word Vectors and Word Senses
작성자 : 투빅스 14기 이혜린 > Contents Word2vec Co-occurrence matrix GloVe Evaluation 1. Word2Vec 텍스트 모델의 핵심은 텍스트를 컴퓨터가 인식할 수 있도록 숫자 형태의 벡터 또는 행렬로 변환하는 것입니다
[CS224n] Lecture 1 - Introduction and Word Vector
작성자 : 투빅스 13기 조혜원 > Contents How to represent Words' Meaning Word2Vec Derivations of Gradient How to represent Words' Meaning 1. WordNet 1) WordNe