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12-text-processing icon 12-text-processing

Day 12 - Finding Needles in Wordstacks: Natural Language Processing and Text Mining

ai-learn icon ai-learn

人工智能学习路线图,整理近200个实战案例与项目,免费提供配套教材,零基础入门,就业实战!包括:Python,数学,机器学习,数据分析,深度学习,计算机视觉,自然语言处理,PyTorch tensorflow machine-learning,deep-learning data-analysis data-mining mathematics data-science artificial-intelligence python tensorflow tensorflow2 caffe keras pytorch algorithm numpy pandas matplotlib seaborn nlp cv等热门领域

bertopic icon bertopic

Leveraging BERT and c-TF-IDF to create easily interpretable topics.

books-1 icon books-1

整理一些书籍 ,包含 C&C++ 、git 、Java、Keras 、Linux 、NLP 、Python 、Scala 、TensorFlow 、大数据 、推荐系统、数据库、数据挖掘 、机器学习 、深度学习 、算法等。

clinical-trial-outcome-prediction icon clinical-trial-outcome-prediction

benchmark dataset and Deep learning method (Hierarchical Interaction Network, HINT) for clinical trial approval probability prediction, accepted by Cell Patterns 2022.

knowledgegraph_agriculture icon knowledgegraph_agriculture

农业领域知识图谱的构建,包括数据爬取(百度百科)、数据分类、利用结构化数据生成三元组、非结构化数据的分句(LTP),分词(jieba),命名实体识别(LTP)、基于依存句法分析(主谓关系等)的关系抽取和利用neo4j生成可视化知识图谱

ldatopicmodelling icon ldatopicmodelling

In this notebook i will be demonstarting Latent Dirchlet Allocation(LDA) for topic modelling. I will be using the Amazon fine food reviews dataset from Kaggle(https://www.kaggle.com/snap/amazon-fine-food-reviews) for performing LDA based topic modelling I will be using the gensim package for LDA topic modelling and pyLDAvis for visualization of LDA topic model

nlp icon nlp

Natural Language Processing pipeline including fundamentals, feature engineering and modeling.

nlp_word_chunking icon nlp_word_chunking

Python code of tokenizing, chunking and pos tagging words in a sentence from a csv file. Used some comments for the project.

nltk-python-cn icon nltk-python-cn

创建《Python自然语言处理》学习代码的中文注释版本。

textmining icon textmining

Python文本挖掘系统 Research of Text Mining System

topic-modeling icon topic-modeling

This repository contains as intuitive example on topic-modeling using regular LDA, and how GuidedLDA is better than regular LDA

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