巴州客服工单自动聚类项目, stars:0, update:2024-06-21 11:36:21 (2024-06-23, Jupyter Notebook, 0KB, 下载0次)
http://www.pudn.com/Download/item/id/1719095523728229.html
朴素贝叶斯文本分类器维基百科
NaiveBayesTextClassifierWikipedia (2024-01-17, Jupyter Notebook, 0KB, 下载0次)
使用贝叶斯方法时KNN传统贝叶斯和KNN贝叶斯的比较
Comparison btw KNN traditional and KNN bayesian while using the bayesian approach (2023-11-08, Jupyter Notebook, 0KB, 下载0次)
凯门斯，，
Kmeans,, (2023-10-28, Jupyter Notebook, 0KB, 下载0次)
凯门斯，，
Kmeans,, (2023-10-07, Jupyter Notebook, 0KB, 下载0次)
凯门斯，，
Kmeans,, (2023-09-18, Jupyter Notebook, 0KB, 下载0次)
萨默维尔分类练习，，
somerville-classification-exercises,, (2023-08-09, Jupyter Notebook, 0KB, 下载0次)
哈萨克斯坦，，
KMEANS,, (2023-08-02, Jupyter Notebook, 0KB, 下载0次)
使用朴素贝叶斯和维基百科API进行文本主题分类，，
Text-Topic-Classification-using-Naive-Bayes-with-Wikipedia-API,, (2023-07-30, Jupyter Notebook, 0KB, 下载0次)
玛丽亚·莎拉波娃、罗杰·费德勒、塞雷娜·威廉姆斯和维拉特·科利。应用Haar级联特征提取和W...
Would like to start with giving due credit to codebasics YouTube channel for the project; to be able to follow it to complete it. Credit to StackOverflow as well for enhancing my learning. The project classifies the image of the sports star: Lionel Messi, Maria Sharapova, Roger Federer, Serena Williams and Virat Kohli. Applied Haar-cascade (2021-10-12, Jupyter Notebook, 110004KB, 下载0次)
维基百科电影情节快速文本
Wikipedia Movie Plots fasttext (2018-12-25, Jupyter Notebook, 64KB, 下载0次)
朴素贝叶斯与拉普拉斯变换，，
Naive-Bayes-with-Laplace-Transform,, (2018-04-01, Jupyter Notebook, 3KB, 下载0次)
使用维德和高斯朴素贝叶斯进行情绪分析
Sentiment Analysis done using Vader and Gaussian Naive Bayes (2023-01-22, Jupyter Notebook, 322KB, 下载0次)
朴素贝叶斯和贝叶斯网络，，
naive-bayes-and-bayesian-network,, (2022-05-19, Jupyter Notebook, 2236KB, 下载0次)
朴素贝叶斯，，
NaiveBayes,, (2021-07-14, Jupyter Notebook, 6KB, 下载0次)
朴素贝叶斯，，
NaiveBayes,, (2022-09-22, Jupyter Notebook, 72KB, 下载0次)
朴素贝叶斯，，
NaiveBayes,, (2020-10-21, Jupyter Notebook, 2308KB, 下载0次)
朴素贝叶斯，，
NaiveBayes,, (2021-10-17, Jupyter Notebook, 567KB, 下载0次)
“稠密嵌入向量的余弦相似保维降维”的笔记本和pytorch模型...
Notebooks and pytorch models for "Cosine similarity preserving dimensionality reduction of dense embedding vectors" talk at ISMB 2022 (2022-08-23, Jupyter Notebook, 3322KB, 下载0次)
服务外包大赛19年选题14-运用文本相似度实现(证券)智能客服【恒生电子】,回笼觉国家队代码
Selected topic of the service outsourcing contest in 19 years 14- use text similarity to achieve (securities) intelligent customer service [Hang Seng Electronics], and recall the national team code (2019-04-29, Jupyter Notebook, 44091KB, 下载0次)