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machine reading comprehension with deep learning
机器学习算法python实现
Learn how to responsibly deliver value with ML.
MAsked Sequence to Sequence (MASS) pre-training for language generation
Facilitating the design, comparison and sharing of deep text matching models.
Aspect Based Sentiment Analysis using End-to-End Memory Networks
meta-learning research
ML and DL related contests, competitions and conference challenges.
机器学习算法 基于西瓜书以及《统计学习方法》,当然包括DL。
此项目是机器学习(Machine Learning)、深度学习(Deep Learning)、NLP面试中常考到的知识点和代码实现,也是作为一个算法工程师必会的理论基础知识。
Papers for deep neural network compression and acceleration
Implementation of model compression with knowledge distilling method.
BiLSTM Distillation with BERT for Sequence CLassification
PyTorch implementation of "Distilling the Knowledge in a Neural Network" for model compression
Models and examples built with TensorFlow
The code for "A Unified MRC Framework for Named Entity Recognition"
Code for `A Unified MRC Framework for Named Entity Recognition`
Classify Kaggle Consumer Finance Complaints into 11 classes. Build the model with CNN (Convolutional Neural Network) and Word Embeddings on Tensorflow.
BERT for multiple span answer RC
Structure-Level Knowledge Distillation For Multilingual Sequence Labeling
Attention-based multimodal fusion for sentiment analysis
django前后端分离项目
Repository of code for the NAACL tutorial on Transfer Learning in NLP
Lstm-crf,Lattice-CRF,bert-ner及近年ner相关论文follow
lstm+crf 实现中文实体识别
基于tensorflow深度学习的中文的命名实体识别
BERT-NER (nert-bert) with google bert https://github.com/google-research.
中文命名实体识别& 中文命名实体检测 python实现 基于字+ 词位 分别使用tensorflow IDCNN+CRF 及 BiLSTM+CRF 搭配词性标注实现中文命名实体识别及命名实体检测
An easy-to-use named entity recognition (NER) toolkit, implemented the Bi-LSTM+CRF model in tensorflow.
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Open source projects and samples from Microsoft.
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