DataKitchen开源数据可观测性产品的安装程序。数据中断。服务器中断。您的工具链断裂。确保您的团队是第一个知道的，也是第一个解决问题的，在整个数据资产中都具有可见性。通过简单、快速的数据质量测试生成和执行节省时间。端到端地信任您的数据、工具和系统。
Installer for DataKitchen s Open Source Data Observability Products. Data breaks. Servers break. Your toolchain breaks. Ensure your team is the first to know and the first to solve with visibility across and down your data estate. Save time with simple, fast data quality test generation and execution. Trust your data, tools, and systems end to end. (2024-04-20, Python, 0KB, 下载0次)
Spotify Scout是一个定制的Discord bot，旨在监控和跟踪Discord服务器内成员的Spotify-Listing活动。该机器人程序与Discord的API集成，以捕获状态更新，并将其记录在MongoDB数据库中，以便随时查询！
Spotify Scout is a custom Discord bot designed to monitor and track Spotify listening activities of members within a Discord server. This bot integrates with Discord s API to capture presence updates and logs them in a MongoDB database to be queried at anytime! (2024-04-01, Python, 0KB, 下载0次)
使用Python的全面Discord机器人程序框架，集成了金融API、OpenAI用于聊天完成的GPT模型，以及用于在Discord服务器中增强交互和数据分析的各种实用程序。用于使用OpenAI和Yahoo Finance分析股市数据
A comprehensive Discord bot framework using Python, integrating finance APIs, OpenAI s GPT models for chat completions, and various utilities for enhanced interaction and data analysis within Discord servers. Used to analyze stock market data using OpenAI and Yahoo Finance (2024-02-21, Python, 0KB, 下载0次)
沼气系统后端是基于烧瓶的web应用程序的服务器端代码，旨在管理和监控沼气相关数据。此后端应用程序提供了一组用于与MySQL数据库交互的API，支持存储和检索与CSV文件、组、收藏夹设置等相关的信息。
The Biogas System Backend is the server-side code for a Flask-based web application designed to manage and monitor biogas-related data. This backend application provides a set of APIs for interacting with a MySQL database, enabling the storage and retrieval of information related to CSV files, groups, favorite settings, and more. (2024-02-13, Python, 0KB, 下载0次)
该项目专注于情感分析，采用两种不同的方法来提高准确性和洞察力：朴素贝叶斯分类器和神经网络模型。这种双重方法旨在利用两种机器学习技术的优势，提供文本数据中情感的综合分析。
This project focuses on sentiment analysis, employing two distinct methodologies for enhanced accuracy and insight: a Naive Bayes Classifier and a neural network model. This dual-approach aims to harness the strengths of both machine learning techniques to provide a comprehensive analysis of sentiment in textual data. (2024-02-02, Python, 0KB, 下载0次)
欢迎来到我的第一个公共Github存储库：一个使用覆盆子Pi 3 B型和Sense帽子的天气监测器。天气数据存储...
Welcome to my first public Github repository: A weather monitor using a Raspberry Pi 3 Model B and a Sense HAT. The weather data is stored in an SQL database, and displayed on a Flask-based website, featuring plots made with matplotlib. (2023-05-01, Python, 0KB, 下载0次)
使用数据挖掘技术，使用每个记录具有250条记录和6个标称属性的数据来预测组织是否容易破产。使用的机器学习技术：线性和非线性SVM、决策树分类器、高斯朴素贝叶斯。
Using data mining techniques to predict if the organization is prone to bankruptcy using the data with 250 records and 6 nominal attributes per record. Machine learning techniques used: Linear and non-linear SVM, Decision Tree Classifier, Gaussian Naive Bayes. (2023-01-06, Python, 0KB, 下载2次)
用于预测Mp3元数据的分类软件###使用数据擦除、数据聚合和数据挖掘的自动Mp3标记编辑器，用于检索给定歌曲的元数据。
A Classification Software for Predicting Mp3 Metadata ### An Automated Mp3 Tag Editor using Data Scraping, Data Aggregation and Data Mining, to retreive metadata for a given song. (2023-07-05, Python, 0KB, 下载0次)
一个简单的Python包装器，用于从Twitter Analytics平台下载推文数据。对于当前TwitterAPI上不可用的印象度量特别有趣。也适用于视频数据。
A simple Python wrapper to download tweets data from the Twitter Analytics platform. Particularly interesting for the impressions metrics that are unavailable on current Twitter API. Also works for the videos data. (2018-12-27, Python, 0KB, 下载0次)
Mining-Frequent-Pattern-from-Search-History,《大数据挖掘技术》@复旦 课程项目,试图从搜狗实验室用户查询日志数据(2008)中找出搜索记录中有较高支持度关键词的频繁二项集。在实现层面上,我搭建了一个由五台服务器组成的微型 Hadoop 集群,并且用 Python 实现了 Par...
Mining Request Pattern from Search History, "Big Data Mining Technology @ Fudan Curriculum Project, attempts to identify frequent binomial sets with high support keywords in search records from Sogou Lab user query log data (2008). At the implementation level, I built a mini Hadoop cluster consisting of five servers and implemented Par in Python (2021-03-29, Python, 1603KB, 下载0次)
程序将能够把用户提供的任何一个图像作为输入。如果可以从图像中检测到一只狗，它会输出对狗品种的预测。如果图像中是一个人脸，它会预测一个与其最相似的狗的种类。
The program will be able to input any image provided by the user. If a dog can be detected from the image, it will output a prediction of dog breed. If the image is a face, it will predict the kind of dog that is most similar to it. (2019-10-04, Python, 589KB, 下载1次)
基于python2X的算法实现, 可以看到，TrAdaBoost算法在源数据和辅助数据具有很多的相似性的时候可以取得很好效果，但是算法也有不足，当开始的时候辅助数据中的样本如果噪声比较多，迭代次数控制的不好，这样都会加大训练分类器的难度。
Based on Python 2X algorithm implementation, we can see that TrAdaBoost algorithm can achieve good results when the source data and auxiliary data have a lot of similarities, but the algorithm also has shortcomings, when the beginning of auxiliary data samples if more noise, iteration control is not good, this will increase the training score. Class is difficult. (2018-09-22, Python, 7KB, 下载3次)