How to Build a T4-Friendly Autonomous Data Science Agent with DeepAnalyze-8B, Sandboxed Code Execution, and Iterative Analysis

Summary

<p>We build an autonomous data science agent around DeepAnalyze-8B and run it end to end. We prepare a stable Colab runtime, install the machine-learning dependencies, and load the tokenizer and model in 4-bit mode to fit limited GPU memory. We add a sandboxed execution environment that lets the model generate Python, run it safely, observe results, and continue in an agentic loop. We then hand the agent a multi-file e-commerce workspace and let it clean, join, analyze, visualize, and summarize the data as an analyst-grade report.</p> <p>The post <a href="https://www.marktechpost.com/2026/07/10/how-to-build-a-t4-friendly-autonomous-data-science-agent-with-deepanalyze-8b-sandboxed-code-execution-and-iterative-analysis/">How to Build a T4-Friendly Autonomous Data Science Agent with DeepAnalyze-8B, Sandboxed Code Execution, and Iterative Analysis</a> appeared first on <a href="https://www.marktechpost.com">MarkTechPost</a>.</p>