RUC-DataLab

DeepAnalyze: Agentic Large Language Models for Autonomous Data Science [](https://arxiv.org/abs/2510.16872) [](https://huggingface.co/papers/2510.16872) [](https://github.com/ruc-datalab/DeepAnalyze) [](https://ruc-deepanalyze.github.io/) [](https://huggingface.co/RUC-DataLab/DeepAnalyze-8B) [](https://huggingface.co/datasets/RUC-DataLab/DataScience-Instruct-500K) > Authors: Shaolei Zhang, Ju Fan, Meihao Fan, Guoliang Li, Xiaoyong Du DeepAnalyze is the first agentic LLM for autonomous data science. It can autonomously complete a wide range of data-centric tasks without human intervention, supporting: - 🛠 Entire data science pipeline: Automatically perform any data science tasks such as data preparation, analysis, modeling, visualization, and report generation. - 🔍 Open-ended data research: Conduct deep research on diverse data sources, including structured data (Databases, CSV, Excel), semi-structured data (JSON, XML, YAML), and unstructured data (TXT, Markdown), and finally produce analyst-grade research reports. - 📊 Fully open-source: The model, code, training data, and demo of DeepAnalyze are all open-sourced, allowing you to deploy or extend your own data analysis assistant.