知凡 (fanfannothing)

fanfannothing

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Company:百度

Location:北京

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知凡's repositories

Awesome-Learning-with-Label-Noise

A curated list of resources for Learning with Noisy Labels

bert_in_keras

在Keras下微调Bert的一些例子;some examples of bert in keras

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nlp_research

基于tensorflow的nlp深度学习项目,支持文本分类/句子匹配/序列标注/文本生成 四大任务

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accum_optimizer_for_keras

wrapping a keras optimizer to implement gradient accumulation

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awesome-python-cn

Python资源大全中文版,包括:Web框架、网络爬虫、模板引擎、数据库、数据可视化、图片处理等,由伯乐在线持续更新。

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awesome-vision-language-pretraining-papers

Recent Advances in Vision and Language PreTrained Models (VL-PTMs)

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Awsome-Deep-Learning-for-Video-Analysis

Papers, code and datasets about deep learning and multi-modal learning for video analysis

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berkeley-stat-157

Homepage for STAT 157 at UC Berkeley

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bert

TensorFlow code and pre-trained models for BERT

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bert4keras

Our light reimplement of bert for keras

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Chinese-Word-Vectors

100+ Chinese Word Vectors 上百种预训练中文词向量

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DALLE-pytorch

Implementation / replication of DALL-E, OpenAI's Text to Image Transformer, in Pytorch

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dgcnn_for_reading_comprehension

keras implement of dgcnn for reading comprehension

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el-2019

2019年百度的实体链接比赛,“科学空间队”源码

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event_extraction

baidu aistudio event extraction competition

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GNN4NLP-Papers

A list of recent papers about Graph Neural Network methods applied in NLP areas.

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keras-bert

Implementation of BERT that could load official pre-trained models for feature extraction and prediction

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keras-contrib

Keras community contributions

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keras_radam

RAdam optimizer for keras

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kg-2019

2019年百度的三元组抽取比赛,“科学空间队”源码

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ML-NLP

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。

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OpenNRE

An Open-Source Package for Neural Relation Extraction (NRE)

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PaddleSeg

Easy-to-use image segmentation library with awesome pre-trained model zoo, supporting wide-range of practical tasks in Semantic Segmentation, Interactive Segmentation, Panoptic Segmentation, Image Matting, 3D Segmentation, etc.

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Python

All Algorithms implemented in Python

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QA-Survey

北航大数据高精尖中心研究团队对问答系统的调研。包括基于知识图谱的问答系统(KBQA)和基于文本的问答系统(TextQA),每类系统分别对学术界和工业界进行调研。

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Research

novel deep learning research works with PaddlePaddle

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summary

The repo will be private and re-open to clear the stars if its number reaches the top 6.

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word-discovery

速度更快、效果更好的中文新词发现

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