该项目旨在比较不同的模型，以预测患者是否患有心脏病。这将通过使用不同的模型来完成，例如（逻辑回归、随机森林、梯度提升、朴素贝叶斯和K-最近邻）。通过评估，将使用最佳模型来预测患者的状态。
This project aims to compare different models to predict whether the patient has a heart disease or not. This will be done by using different models such as (Logistic Regression, Random Forest, Gradient Boosting, Na ve Bayes, and K-Nearest Neighbors). By evaluating them, the best model will be used to predict the status of the patient. (2024-05-14, HTML, 0KB, 下载0次)
能源市场和数据分析学期项目，罗格斯大学，2024年春季。使用来自IEEE混合能源预测和交易竞争的数据来创建预测模型，应用保角建模来获得概率预测，并使用条件风险值来优化能源交易的利润。
Semester Project for Energy Markets and Data Analytics, Rutgers, Spring 2024. Uses data from IEEE Hybrid Energy Forecasting and Trading Competition to create a forecasting model, apply conformal modeling to obtain probabilistic forecasts, and use conditional value at risk to optimize profits for energy trading. (2024-04-22, HTML, 0KB, 下载0次)
本课程涵盖概率机器学习的概念：独立性、条件独立性、混合模型、EM算法、贝叶斯网络、潜在线性模型以及精确和近似推理的算法，重点是变分推理，这有助于推导复杂模型的近似推理算法
The course covers concepts in probabilistic machine learning: independence, conditional independence, mixture models, EM algorithm, Bayesian networks, latent linear models, and algorithms for exact and approximate inference, with an emphasis on variational inference, which helps derive approximate inference algorithms for complex models (2024-04-02, HTML, 0KB, 下载0次)
设计了一个基于机器学习的系统，用于将可执行文件分类为恶意或合法。为项目使用了各种算法，包括决策树、AdaBoost、梯度提升、朴素贝叶斯和随机森林。使用随机森林算法实现了99.40%的最高精度。
Engineered a machine learning-based system for classifying executable files as malicious or legitimate. Utilized various algorithms for the project including Decision Tree, AdaBoost, Gradient Boosting, Naive Bayes, and Random Forest. Achieved the highest accuracy of 99.40% with the Random Forest algorithm. (2024-03-25, HTML, 0KB, 下载0次)
应用以下技术研究数据科学家角色的薪酬：QDA、LDA、朴素贝叶斯方法、随机森林、KNN、SVM、（Logistic、Lasso和Ridge）回归和弹性网络。此外，考虑线性、简单和多元模型的数据库研究。
Study about salaries in data scientists roles applying the following techniques: QDA, LDA, Naive-Bayes approach, Random Forests, KNN, SVM, (Logistic, Lasso and Ridge) Regression and Elastic Nets. Also, study of the database considering linear, simple and multivariate models. (2024-03-12, HTML, 0KB, 下载0次)
Egalitédes hommes et des femmes:$b玛丽·勒·贾斯·德·古尔奈（Marie Le Jars de Gournay）的《雷恩》（la Reyne）是一本古腾堡计划（Project Gutenberg）的书，现在是关于吉图布（Github）的。
Egalité des hommes et des femmes : $b A la Reyne by Marie Le Jars de Gournay is a Project Gutenberg book, now on Github. (2023-12-26, HTML, 0KB, 下载0次)
垃圾邮件SMS检测模型是一种使用朴素贝叶斯算法来识别和分类垃圾邮件的强大解决方案。附带的Flask界面为用户提供了提交SMS条目、跟踪使用情况和接收实时分类结果的无缝体验。
Spam SMS Detection model is a powerful solution built to identify and classify spam messages using the Naive Bayes algorithm. The accompanying Flask interface provides users with a seamless experience for submitting SMS entries, tracking usage, and receiving real-time classification results. (2023-12-21, HTML, 0KB, 下载0次)