Coursera, Deep Learning 5, Sequence Models, week2, Natural Language Processing & Word Embeddings

文章名<Deepening Hidden Representations from Pre-trained Language Models for Natural Language Understanding>,2019,单位:上海交大 从预训练语言模型中深化语言表示 摘要:基于Transformer的预训练语言模型已经被证明在语境化语言表征方面是有效的,然而,当前的方法在下游任务的微调过程中都仅仅是利用编码器的最后一层输出信息.那么,只是单纯的利用单一层的输出会限制预训练表征的能力,因此,我

A curated list of speech and natural language processing resources At Josh.ai, we’re often asked for developer resources relating to natural language processing, machine learning, and artificial intelligence. Paul Dixon, a researcher living in Kyoto

基于python 自然语言处理工具包 :NLPT(natural language processing toolkit)  ,安装时 sudo pip -U install nltk NLPT的网址 Natural language processing toolkits Name Language License Creators Website Apertium C++, Java GPL (various) [1] Deeplearning4j Java, Scala Apache 2.

一年之前,我做梦也想不到会来这里写技术总结.误打误撞来到了上海西南某高校,成为了文科专业的工科男,现在每天除了膜ha,就是恶补CS.导师是做计算语言学的,所以当务之急就是先自学计算机自然语言处理,打好底子准备做科研(认真脸). 进入正题,从图书馆找了本“Natural Language Processing with Python” (影印版),书长这个样子,作者是Steven Bird, Ewan Klein和Edward Loper.粘贴个豆瓣链接供参考:https://book.douba

CNN 主要解决 computer vision 问题,同时解决input X 维度太大的问题. Edge detection example 演示了convolution 的概念 下图的 vertical edge 看起来有点厚,但是如果图片远比6x6像素大的话,就会看到效果非常不错. 原文地址:https://www.cnblogs.com/mashuai-191/p/8660722.html

https://github.com/kjw0612/awesome-rnn#natural-language-processing 通常有: (1)Object Recognition (2)Visual Tracking (3)Image Generation (4)Video Analysis NLP: (1)Language Modeling (2)Speech Recognition (3)Machine Translation (4)Conversation Modeling (5)

用Enthought Canopy作图果然方便.昨天频频出现无法识别pylab模块的异常,今天终于搞好了.以下是今天出来的图:

Sequence Models This is the fifth and final course of the deep learning specialization at Coursera which is moderated by deeplearning.ai Here are the course summary as its given on the course link: This course will teach you how to build models for n

About this Course This course will teach you how to build models for natural language, audio, and other sequence data. Thanks to deep learning, sequence algorithms are working far better than just two years ago, and this is enabling numerous exciting