第二周 自然语言处理与词嵌入(Natural Language Processing and Word Embeddings) 词汇表征(Word Representation) 上周我们学习了 RNN.GRU 单元和 LSTM 单元.本周你会看到我们如何把这些知识用到 NLP 上,用于自然语言处理,深度学习已经给这一领域带来了革命性的变革.其中一个很关键的概念就是词嵌入(word embeddings),这是语言表示的一种方式,可以让算法自动的理解一些类似的词,比如男人对女人,比如国王对王后,…

Week 2 Quiz: Natural Language Processing and Word Embeddings (第二周测验:自然语言处理与词嵌入) 1.Suppose you learn a word embedding for a vocabulary of 10000 words. Then the embedding vectors should be 10000 dimensional, so as to capture the full range of variation…

第二周 自然语言处理与词嵌入(Natural Language Processing and Word Embeddings) 2.1 词汇表征(Word Representation) 词汇表示,目前为止一直都是用词汇表来表示词,上周提到的词汇表,可能是 10000 个单词,我们一直用 one-hot 向量来表示词.这种表示方法的一大缺点就是它把每个词孤立起来,这样使得算法对相关词的泛化能力不强. 换一种表示方式会更好,如果不用 one-hot 表示,而是用特征化的表示来表示每个词,man,w…

Speech and Natural Language Processing obtain from this link: https://github.com/edobashira/speech-language-processing A curated list of speech and natural language processing resources. Other lists can be found in this list. If you want to contribut…

https://www.programmableweb.com/news/how-5-natural-language-processing-apis-stack/analysis/2014/07/28 The world is awash in digital data. The challenge: making sense of that data. To tackle that challenge, a growing number of companies are turning to…

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…

spaCy is a library for advanced natural language processing in Python and Cython. spaCy is built on the very latest research, but it isn't researchware. It was designed from day one to be used in real products. spaCy currently supports English, Germa…

CS224n: Natural Language Processing with Deep Learning http://cs224d.stanford.edu/syllabus.html https://web.stanford.edu/class/cs224n/syllabus.html 论文 https://web.stanford.edu/class/archive/cs/cs224n/cs224n.1174/reports.html…

-<Natural Language Processing with Python> 链接:https://pan.baidu.com/s/1_oalRiUEw6bXbm2dy5q_0Q 密码:r318…

Operations on word vectors Welcome to your first assignment of this week! Because word embeddings are very computionally expensive to train, most ML practitioners will load a pre-trained set of embeddings. After this assignment you will be able to: L…

http://www.nltk.org/book/ch00.html After this, the pace picks up, and we move on to a series of chapters covering fundamental topics in language processing: tagging, classification, and information extraction (Chapters 5-7). The next three chapters l…

Spoken input (top left) is analyzed, words are recognized, sentences are parsed and interpreted in context, application-specific actions take place (top right); a response is planned, realized as a syntactic structure, then to suitably inflected word…

Operations on word vectors Welcome to your first assignment of this week! Because word embeddings are very computionally expensive to train, most ML practitioners will load a pre-trained set of embeddings. After this assignment you will be able to: L…

Word embeding 给word 加feature,用来区分word 之间的不同,或者识别word之间的相似性. 用于学习 Embeding matrix E 的数据集非常大,比如 1B - 100B 的word corpos. 所以即使你输入的是没见过的 durian cutivator 也知道和 orange farmer 很相近. 这是transfter learning 的一个case. 因为t-SNE 做了non-liner 的转化,所以在原来的300维空间的平行的向量在转化过后…

Emojify! Welcome to the second assignment of Week 2. You are going to use word vector representations to build an Emojifier. Have you ever wanted to make your text messages more expressive? Your emojifier app will help you do that. So rather than wri…

[解释] The dimension of word vectors is usually smaller than the size of the vocabulary. Most common sizes for word vectors ranges between 50 and 400. [解释] 过用t-SNE算法来将单词可视化.t-SNE算法所做的就是把这些n维的数据用一种非线性的方式映射到2维平面上,可以得知t-SNE中这种映射很复杂而且很非线性. [解释] Yes, word v…

课程学习中心 | NLP课程合辑 | 课程主页 | 中英字幕视频 | 项目代码解析 课程介绍 自然语言处理 (NLP) 是一门关于如何教计算机理解人类语言的工程艺术和科学.NLP 作为一种人工智能技术,现在已经无处不在--我们可以与手机交谈.使用网络回答问题.在社交媒体中讨论,甚至在人类语言之间进行翻译. CS685 马萨诸塞大学 NLP 进阶课程,广泛关注自然语言处理的深度学习方法,详细讲解前沿技术点与典型应用.课程重点是神经语言模型和迁移学习--这两者都极大地推动了最先进的技术. 课程基于…

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)…

Distributed Representations of Words and Phrases and their Compositionality T Mikolov, I Sutskever, K Chen, G Corrado, J Dean Advances in Neural Information Processing Systems, 2013, 26:3111-3119. LINE: Large-scale Information Network Embedding Jian…

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:…

什么是深度学习?   一种机器学习算法,based on [多层][非线性变换]的[神经网络]结构 优点:可以使用 低维 稠密 连续 的向量表示不同粒度的语言单元, 还可以使用循环.卷积.递归等神经网络模型对不同的语言单元向量进行组合,获得更大的语言单元, 甚至可以将图像.语言等不同的东西表示在同一个语义向量空间中 ===================================== 1. Robust, 鲁棒性,健壮性,指系统稳定,抗风险,比如面对训练数据有部分异常值,依然可以表现稳定.…

自然语言处理 - 维基百科,自由的百科全书 https://zh.wikipedia.org/wiki/%E8%87%AA%E7%84%B6%E8%AF%AD%E8%A8%80%E5%A4%84%E7%90%86 BEST PRACTICE 语音识别技术简史 https://mp.weixin.qq.com/s/wnPAnOaB0ydahZP-Da4Plw NLP领域预训练模型的现状及分析 https://mp.weixin.qq.com/s/vFsJE81Rs8C1zKoNv3K-bA 自然语…

cs224n 斯坦福网址,里面包含讲课视频,ppt,代码,学习完后做一个问答系统 http://web.stanford.edu/class/cs224n/index.html 下载anaconda,里面包含python和python第三方的包,pytorch https://repo.anaconda.com/archive 下载pycharm 或者 jupyter word2vec图解(原文翻译) https://mp.weixin.qq.com/s/Yq_-1eS9UuiUBhNNAIxC…

NLP自然语言处理: 百度AI的 NLP自然语言处理python语言--pythonSDK文档: https://ai.baidu.com/docs#/NLP-Python-SDK/top 第三方模块:pip install baidu-aip NLP_test.py from aip import AipNlp """ 你的 APPID AK SK """ APP_ID = ' API_KEY = 'jM4b8GIG9gzrzySTRq3szK…

http://delivery.acm.org/10.1145/220000/218367/p543-brill.pdf?ip=116.30.5.154&id=218367&acc=OPEN&key=4D4702B0C3E38B35.4D4702B0C3E38B35.4D4702B0C3E38B35.6D218144511F3437&CFID=763856971&CFTOKEN=66313413&acm=1495021097_b5bf093135456075…

2 Natural Language Processing & Word Embeddings 2.1 Word Representation(单词表达) vocabulary,每个单词可以使用1-hot表示,写作\(O^{5391}\)之类,上标可以变.只是用1-hot,不能知道任意两个单词的关系,例如man/woman;king/queen;apple/orange. 特征化表示:词嵌入(Featurized representation:word embedding).一个特征,使用-1到…

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…

Building your Recurrent Neural Network - Step by Step Welcome to Course 5's first assignment! In this assignment, you will implement your first Recurrent Neural Network in numpy. Recurrent Neural Networks (RNN) are very effective for Natural Language…

Building your Recurrent Neural Network - Step by Step Welcome to Course 5's first assignment! In this assignment, you will implement your first Recurrent Neural Network in numpy. Recurrent Neural Networks (RNN) are very effective for Natural Language…