MorvanZhou/NLP-Tutorials is ranked 12,422 among these 8 peers; gabrieleangeletti/Deep-Learning-TensorFlow is ranked 12,411.

Natural Language Processing Tutorial Tutorial in Chinese can be found in mofanpy. This repo includes many simple implementations of models in Neural Language Processing (NLP). All code implementations in this tutorial are organized as following: 1. Search Engine TF-IDF numpy / TF-IDF skearn 2. Understand Word (W2V) Continuous Bag of Words (CBOW) Skip-Gram 3. Understand Sentence (Seq2Seq) seq2seq CNN language model 4. All about Attention seq2seq with attention Transformer 5. Pretrained Models ELMo GPT BERT Thanks for the

contribution made by @W1Fl with a simplified keras codes in simple_realize. And the a pytorch version of this NLP tutorial made by @ruifanxu. Installation TF-IDF TF-IDF numpy code TF-IDF short sklearn code Word2Vec Efficient Estimation of Word Representations in Vector Space Skip-Gram code CBOW code Seq2Seq Sequence to Sequence Learning with Neural Networks Seq2Seq code CNNLanguageModel Convolutional Neural Networks for Sentence Classification CNN language model code Seq2SeqAttention Effective Approaches to Attention-based Neural Machine Translation

Seq2Seq Attention code Transformer Attention Is All You Need Transformer code ELMO Deep contextualized word representations ELMO code GPT Improving Language Understanding by Generative Pre-Training GPT code BERT BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding BERT code My new attempt Bert with window mask