LLM能替代数据科学家了？DeepAnalyze帮你告别手动分析数据

Core Insights - DeepAnalyze is introduced as a specialized "data scientist" that automates data analysis and various data science tasks with a single command [1][5] - The tool supports automated data preparation, analysis, modeling, visualization, and insights generation [3] - DeepAnalyze is the first Agentic LLM designed for data science, capable of independently completing complex data tasks without predefined workflows [5][6] Data Science Tasks - DeepAnalyze can perform automated data preparation, analysis, modeling, visualization, and insights generation [3] - It is capable of conducting open-ended deep research across unstructured, semi-structured, and structured data, generating comprehensive research reports [3][16] Training Methodology - DeepAnalyze employs a curriculum-based Agentic training paradigm to enable LLMs to autonomously complete complex data science tasks [10][12] - The training process consists of two phases: single capability fine-tuning and multi-capability Agentic training in real task environments [13] Curriculum-Based Agentic Training - This training method simulates the learning path of human data scientists, allowing LLMs to progress from simple to complex tasks [12] - It addresses the "sparse reward" problem in reinforcement learning, ensuring that models receive positive feedback during training [11][12] Data-Grounded Trajectory Synthesis - DeepAnalyze introduces a method for synthesizing 500,000 data science reasoning and interaction trajectories to guide LLMs in solving long-chain problems [14] - This synthesis includes reasoning trajectory synthesis and interaction trajectory synthesis, providing effective guidance for LLMs in exploring solution spaces [15] Research Capabilities - DeepAnalyze can automatically generate research reports that meet analyst standards, outperforming existing closed-source LLMs in both content depth and report structure [16]