Data repository for pretrained NLP models and NLP corpora.
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Updated
Mar 16, 2018 - Python
Data repository for pretrained NLP models and NLP corpora.
Data Science algorithms and topics that you must know. (Newly Designed) Recommender Systems, Decision Trees, K-Means, LDA, RFM-Segmentation, XGBoost in Python, R, and Scala.
Using latent Dirichlet allocation (LDA) in Apache Lucene
A tool to suggest github repositories based on the repositories you have shown interest in.
This Python project develops a LDA model which trains on various Wikipedia articles based on a keyword and then suggests Wikipedia articles based on a search query.
Code to run LDA algorithm on Twitter/Foursquare scraped data.
针对微博平台的微博文本数据进行舆情分析项目,内容有微博爬虫、LDA主题分析和情感分析
NLP of Ted Talk transcripts and a recommender.
对汽车之家论坛里的评论数据处理和分析,利用用户潜在行为数据得出用户行为特征,采用LDA主题模型得出用户评论的主题特征,采用Word2Vec词向量模型得出用户评论的文本内容特征,采用K-Means聚类得出水军文本类别,结合用户行为特征,最终实现了对网络水军的识别。
A consolidated collection of topic model implementations
Use Word2vec model and LDA model for drug recommendation
Extracting Hidden Topics from Texts using LDA Model
Algorithms for tensor decomposition in GMM, LDA topic models etc.
REST web service to compute and query Latent Dirichlet Allocation models
An approach to organize text data generated from URLs by tagging it to facilitate data cataloging while maintaining the DCAT standards. Topic modeling algorithm 'LDA' is used for classifying data by finding best descriptor tags based on the content automatically.
Topic modelling - optimization of model hyper params. Notebooks are examples of using our optimization pipeline for sample data.
An NLP project that compares different approaches to document representation and classification. The techniques used include Topic-modeling, Tf-Idf, doc2vec, SVM, and CNN
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