scikit-learn: machine learning in Python
Repository Index
47,133 repositories indexed
1–16 of 16 · Most stars
⭐AI-driven public opinion & trend monitor with multi-platform aggregation, RSS, and smart alerts.🎯 告别信息过载，你的 AI 舆情监控助手与热点筛选工具！聚合多平台热点 + RSS 订阅，支持关键词精准筛选。AI 智能筛选新闻 + AI 翻译 + AI 分析简报直推手机，也支持接入 MCP 架构，赋能 AI 自然语言对话分析、情感洞察与趋势预测等。支持 Docker ，数据本地/云端自持。集成微信/飞书/钉钉/Telegram/邮件/ntfy/bark/slack 等渠道智能推送。
- data-analysis
- python
- trending-topics
- news
Streamlit — A faster way to build and share data apps.
Build and share delightful machine learning apps, all in Python. 🌟 Star to support our work!
- machine-learning
- models
- ui
- ui-components
微舆：人人可用的多Agent舆情分析助手，打破信息茧房，还原舆情原貌，预测未来走向，辅助决策！从0实现，不依赖任何框架。
- agent-framework
- data-analysis
- multi-agent-system
- nlp
Chat with your database or your datalake (SQL, CSV, parquet). PandasAI makes data analysis conversational using LLMs and RAG.
1 Line of code data quality profiling & exploratory data analysis for Pandas and Spark DataFrames.
- pandas-profiling
- pandas-dataframe
- statistics
- jupyter-notebook
Always know what to expect from your data.
- pipeline-tests
- dataquality
- datacleaning
- datacleaner
Cleanlab's open-source library is the standard data-centric AI package for data quality and machine learning with messy, real-world data and labels.
- weak-supervision
- data-cleaning
- data-quality
- noisy-labels
Open Machine Learning Course
A Python Package to Tackle the Curse of Imbalanced Datasets in Machine Learning
Visualize and compare datasets, target values and associations, with one line of code.
- pandas-dataframe
- eda
- pandas
- data-exploration
What's in your data? Extract schema, statistics and entities from datasets
- python
- privacy
- pii
- npi
:truck: Agile Data Preparation Workflows made easy with Pandas, Dask, cuDF, Dask-cuDF, Vaex and PySpark
NFStream: a Flexible Network Data Analysis Framework.
- data-science
- data-analysis
- data-mining
- network-analysis
A lightweight Python package for teaching computational methods through art history. Extract and analyze artist-specific works from WikiArt with built-in visualizations. Designed for digital humanities and computational design courses. Features genre/style analysis, matplotlib integration, and pedagogical clarity over algorithmic complexity.
- art-history
- color-analysis
- color-extraction
- color-palette