All Git Users → yuanxiaosc

13 open source projects by yuanxiaosc

1. Schema Based Knowledge Extraction
Code for http://lic2019.ccf.org.cn/kg 信息抽取。使用基于 BERT 的实体抽取和关系抽取的端到端的联合模型。
2. Theoretical Proof Of Neural Network Model And Implementation Based On Numpy
This resource implements a deep neural network through Numpy, and is equipped with easy-to-understand theoretical derivation, mainly for the in-depth understanding of neural networks. 神经网络模型的理论证明与基于Numpy的实现。
3. Multimodal Short Video Dataset And Baseline Classification Model
500,000 multimodal short video data and baseline models. 50万条多模态短视频数据集和基线模型(TensorFlow2.0)。
4. Xlnet paper chinese translation
XLNet: Generalized Autoregressive Pretraining for Language Understanding 论文的中文翻译 Paper Chinese Translation!
5. Machine learning bookshelf
机器学习深度学习相关书籍、课件、代码的仓库。 Machine learning is the warehouse of books, courseware and codes.
6. Entity Relation Extraction
Entity and Relation Extraction Based on TensorFlow and BERT. 基于TensorFlow和BERT的管道式实体及关系抽取,2019语言与智能技术竞赛信息抽取任务解决方案。Schema based Knowledge Extraction, SKE 2019
7. Machine Learning Book
《机器学习宝典》包含:谷歌机器学习速成课程(招式)+机器学习术语表(口诀)+机器学习规则(心得)+机器学习中的常识性问题 (内功)。该资源适用于机器学习、深度学习研究人员和爱好者参考!
8. Bert paper chinese translation
BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding 论文的中文翻译 Chinese Translation!
9. Deepnude An Image To Image Technology
DeepNude's algorithm and general image generation theory and practice research, including pix2pix, CycleGAN, UGATIT, DCGAN, SinGAN, ALAE, mGANprior, StarGAN-v2 and VAE models (TensorFlow2 implementation). DeepNude的算法以及通用生成对抗网络(GAN,Generative Adversarial Network)图像生成的理论与实践研究。
10. Bert For Sequence Labeling And Text Classification
This is the template code to use BERT for sequence lableing and text classification, in order to facilitate BERT for more tasks. Currently, the template code has included conll-2003 named entity identification, Snips Slot Filling and Intent Prediction.
11. Multiple Relations Extraction Only Look Once
Multiple-Relations-Extraction-Only-Look-Once. Just look at the sentence once and extract the multiple pairs of entities and their corresponding relations. 端到端联合多关系抽取模型,可用于 http://lic2019.ccf.org.cn/kg 信息抽取。
12. yuanxiaosc.github.io
个人博客;论文;机器学习;深度学习;Python学习;C++学习;
13. fan-ren-xiu-xian-zhuan
凡人修仙传(fanrenxiuxianzhuan)的资源汇总,谨献给“凡友”们。
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