使用归入NLP（即自然语言处理）的文本摘要创建总结新闻相关文本的应用程序
To create an app that summarizes text related to news using Text Summarization which falls under NLP i.e. Natural Language Processing (2024-04-02, Jupyter Notebook, 0KB, 下载0次)
使用NLP技术和ML算法对阿拉伯语报刊或新闻文章进行自动分类
Automatic classification of Arabic press or news articles using NLP techniques and ML algorithms (2024-04-01, Others, 0KB, 下载0次)
ICKDP代码（局部中心密度峰值聚类和改进的连通性核，2024）
code of ICKDP（Density peak clustering by local centers and improved connectivity kernel，2024） (2024-04-01, matlab, 0KB, 下载1次)
“购物中心客户细分”采用KMeans聚类来分析超市购物中心的客户数据。通过根据年龄、性别、收入和消费习惯对客户进行分类，该项目确定了定制营销战略的目标群体，为有效的客户细分技术提供了宝贵的见解。
"Mall Customer Segmentation" employs KMeans clustering to analyze customer data from a supermarket mall. By categorizing customers based on age, gender, income, and spending habits, the project identifies target groups for tailored marketing strategies, offering valuable insights into effective customer segmentation techniques. (2024-04-01, Others, 0KB, 下载0次)
新闻分类采用NLP和机器学习技术来自动将新闻文章分类为假新闻或真新闻。
News classification employes NLP and machine learning techniques to automatically categorize news articles into fake or real news. (2024-03-30, Jupyter Notebook, 0KB, 下载0次)
基于NLP的文本摘要生成器使用高级NLP方法将长文本浓缩为简明摘要。它提供可定制的参数、实时多文档摘要，并在新闻、文档、内容管理和教育中找到应用程序，从而提高生产力。
NLP-Based Text Summarizer condenses long texts into concise summaries using advanced NLP methods. It offers customizable parameters, real-time multi-document summarization, and finds applications in news, documents, content curation, and education, enhancing productivity. (2024-03-31, Python, 0KB, 下载0次)
我们的基于NLP的文本摘要生成器使用高级NLP方法将长文本压缩为简明摘要。它提供可定制的参数、实时多文档摘要，并在新闻、文档、内容管理和教育中找到应用程序，从而提高生产力。
Our NLP-Based Text Summarizer condenses long texts into concise summaries using advanced NLP methods. It offers customizable parameters, real-time multi-document summarization, and finds applications in news, documents, content curation, and education, enhancing productivity. (2024-03-31, Python, 0KB, 下载0次)
使用购物中心客户数据集的KMeans细分
KMeans Segmentation Using Mall Customer Dataset (2024-03-29, Jupyter Notebook, 0KB, 下载0次)
使用Logistic回归和量瓶为用户交互开发了一个92%准确率的假新闻预测器。根据严格的数据分析，设计了一个精确的系统来评估新闻内容，以绿色表示真实新闻，以红色表示虚假新闻。
Developed a Fake News Predictor with 92% accuracy using Logistic Regression and Flask for user interaction. Engineered a precise system that evaluates news content, signaling green for authentic news and red for fake news based on rigorous data analysis. (2024-03-30, HTML, 0KB, 下载0次)
为学习和娱乐编写此代码！
code this for learning and fun! (2024-03-29, C++, 0KB, 下载0次)
新闻聚类
news clustering (2024-03-29, Python, 0KB, 下载0次)
基于朴素贝叶斯技术的假新闻检测模型
Fake News Detection model using Naive Bayes technique (2024-03-29, Others, 0KB, 下载0次)
一种检测假新闻的决策树算法。
A decision tree algorithm to detect fake news. (2024-03-25, Python, 0KB, 下载0次)
ML-KNN-LinearLassoRidge项目的中心是实现K-Nearest Neighbors（K-NN）分类器，并探索各种回归技术，包括线性回归、套索回归和岭回归。这些算法被应用于机器学习中的分类和回归任务。
The ML-KNN-LinearLassoRidge project is centered around implementing the K-Nearest Neighbors (K-NN) Classifier and exploring various regression techniques including linear regression, lasso regression, and ridge regression. These algorithms are applied to tackle classification and regression tasks in machine learning. (2024-03-23, Others, 0KB, 下载0次)
这使用Streamlit定义了一个新闻摘要web应用程序，允许用户访问和阅读来自各种来源的新闻文章。下面是项目所做工作的摘要—导入必要的Python库，包括用于web应用程序的Streamlit、用于web抓取的BeautifulSoup、用于图像处理的PIL。
This defines a news summarization web application using Streamlit, allowing users to access and read news articles from various sources. Here s an abstract of what the project does the necessary Python libraries are imported, including Streamlit for the web application, BeautifulSoup for web scraping, PIL for image processing. (2024-03-21, Python, 0KB, 下载0次)
一种基于基本机器学习的新闻检测器，用于识别新闻文章的真实性。使用了Pasiive-Aggressive、朴素贝叶斯、支持向量机和随机森林等算法。
A basic machine learning based News detector to identify the authencity of the news articles. Algorithms like Pasiive-Aggressive, Naive Bayes, Support Vector Machine and Random Forest were used. (2024-03-16, Jupyter Notebook, 0KB, 下载0次)
NLP摘要生成器浓缩文本，提取新闻、文档和内容管理的关键信息。它们有助于决策，改善搜索，增强可访问性，促进学术界和专业界的生产力。
NLP summarizers condense text, extracting key info for news, documents, and content curation. They aid decision-making, improve search, and enhance accessibility, fostering productivity across academia and professions. (2024-03-15, Jupyter Notebook, 0KB, 下载0次)
k-PbC：一种改进的分类数据聚类聚类中心初始化方法
k-PbC: An Improved Cluster Center Initialization for Categorical Data Clustering (2024-03-12, Jupyter Notebook, 0KB, 下载0次)
泰米尔语新闻分类
Tamil News Classification (2024-03-10, Jupyter Notebook, 0KB, 下载0次)
该回购具有用于新闻文章分类和医疗保险成本回归的K-Nearest Neighbor（KNN）实现。利用词袋模型，它展示了KNN在分类和估计任务中的通用性。
This repo features K-Nearest Neighbor (KNN) implementations for news article classification and medical insurance cost regression. Utilizing a Bag of Words model, it demonstrates KNN s versatility in both categorization and estimation tasks. (2024-03-09, Jupyter Notebook, 0KB, 下载0次)