promisingFish's starred repositories
pytorch-relation-extraction
distant supervised relation extraction models: PCNN MIL (Zeng 2015), PCNN+ATT(Lin 2016). 关系抽取
TorchGlove
PyTorch implementation of Global Vectors for Word Representation.
yelp_comments_classification_nlp
Yelp round-10 review comments classification using deep learning (LSTM and CNN) and natural language processing.
deep-learning-v2-pytorch
Projects and exercises for the latest Deep Learning ND program https://www.udacity.com/course/deep-learning-nanodegree--nd101
course-nlp
A Code-First Introduction to NLP course
cnn-text-classification-pytorch
CNNs for Sentence Classification in PyTorch
nlp_chinese_corpus
大规模中文自然语言处理语料 Large Scale Chinese Corpus for NLP
clip-as-service
🏄 Scalable embedding, reasoning, ranking for images and sentences with CLIP
100-Days-Of-ML-Code
100 Days of ML Coding
ABSA-PyTorch
Aspect Based Sentiment Analysis, PyTorch Implementations. 基于方面的情感分析，使用PyTorch实现。
NLP-progress
Repository to track the progress in Natural Language Processing (NLP), including the datasets and the current state-of-the-art for the most common NLP tasks.
Awesome-pytorch-list
A comprehensive list of pytorch related content on github,such as different models,implementations,helper libraries,tutorials etc.
list_of_recommender_systems
A List of Recommender Systems and Resources
Awesome-Chinese-NLP
A curated list of resources for Chinese NLP 中文自然语言处理相关资料
awesome-nlp
:book: A curated list of resources dedicated to Natural Language Processing (NLP)
awesome-deep-learning-papers
The most cited deep learning papers
nlp-tutorial
Natural Language Processing Tutorial for Deep Learning Researchers
tweet-stance-prediction
Applying NLP transfer learning techniques to predict Tweet stance toward a topic
attention-is-all-you-need-pytorch
A PyTorch implementation of the Transformer model in "Attention is All You Need".
Text-Classification
Text Classification through CNN, RNN & HAN using Keras
deeplearning-papernotes
Summaries and notes on Deep Learning research papers
DeepLearning-500-questions
深度学习500问，以问答形式对常用的概率知识、线性代数、机器学习、深度学习、计算机视觉等热点问题进行阐述，以帮助自己及有需要的读者。 全书分为18个章节，50余万字。由于水平有限，书中不妥之处恳请广大读者批评指正。 未完待续............ 如有意合作，联系scutjy2015@163.com 版权所有，违权必究 Tan 2018.06
Hands-On-Deep-Learning-with-TensorFlow
Hands-On Deep Learning with TensorFlow, published by Packt