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article_clustering

article clustering with doc2vec in Chinese

blog-doc2vec

Code accompanying blog posts about doc2vec

book

Deep Learning 101 with PaddlePaddle （『飞桨』深度学习框架入门教程）

chinese_text_cluster

MachineLearning

cluecorpus2020

Large-scale Pre-training Corpus for Chinese 100G 中文预训练语料

clustering

Clustering / Subspace Clustering Algorithms on MATLAB

clustering_algorithms-kmeans

Implementing Clustering Algorithms in Python (NumPy): K-Means Clustering

data-mining

中文文本分类与聚类

differential-privacy-library

Diffprivlib: The IBM Differential Privacy Library

document-classification-using-lsa

Document classification using Latent semantic analysis in python

hac-text-clustering

It's the HAC algorithm that Im using to sort newspaper articles by news. You can adapt it to pretty much any type of text.

hello-world

jiagu

Jiagu深度学习自然语言处理工具 知识图谱关系抽取 中文分词 词性标注 命名实体识别 情感分析 新词发现 关键词 文本摘要 文本聚类

keyword_extraction

利用Python实现中文文本关键词抽取，分别采用TF-IDF、TextRank、Word2Vec词聚类三种方法。

kmeans

K Means Clustering with Python

kmeans-clustering---scikit-learn

A quick tutorial on KMeans clustering in Python.

kmeans-emails-clustering-visualization-nlp

KMeans-Emails-Clustering-Visualization-NLP: KMeans is used to cluster the emails. The words in the contents of emails are tokenlized and stemmed. This project transforms the corpus into vector space using tf-idf.By multidimensional scaling, the clustering result is visualized.

kmeans_elbow

Code for determining optimal number of clusters for K-means algorithm using the 'elbow criterion'

learning-nlp

nlp in action

matplotlib

matplotlib: plotting with Python

native-kmeans-algorithm

Provides the algorithm of kMeans Clustering without Sklearn

news-documents-clustering

News documents clustering using latent semantic analysis

nlp-project-book-insights-with-plotly

Plotly-Dash NLP project. Document similarity measure using Latent Dirichlet Allocation, principal component analysis and finally follow with KMeans clustering. Project is completed with dynamic visual interaction.

optimization-of-kmeans-algorithm

K-Means is a clustering algorithm which is used for cluster analysis in data mining; it partitions the data set into k clusters. In this project, K-Means algorithm is optimized using PSO (Parm Swarm Optimization)in terms of time. PSO simulates the social behavior of birds and helps to improve candidate solution iteratively. This project is made in python and has been tested on some standard data sets.

quickstart

百度AI平台QuickStart文档配套代码

scikit-learn

scikit-learn: machine learning in Python

text_analysis_tools

中文文本分析工具包（包括- 文本分类 - 文本聚类 - 文本相似性 - 关键词抽取 - 关键短语抽取 - 情感分析 - 文本纠错 - 文本摘要 - 主题关键词-同义词、近义词）

text_cluster_ensemble

文本聚类集成，使用K-Means获得聚类成员，使用组平均的层次聚类算法对共协矩阵再次划分;数据集从复旦大学中文文本分类语料库中选取

textinfoexp

自然语言处理实验（sougou数据集），TF-IDF，文本分类、聚类、词向量、情感识别、关系抽取等

tweet-clustering

Embedding Tweets using Doc2Vec (vectorizer) and clustering tweet vectors using Kmeans