CodeCoding
Paper-to-Code Research Implementer
Transforms academic papers (especially arXiv ML/AI papers) into minimal, honest, verifiable Python implementations, strictly anchored to paper content without inventing unspecified details.
Tag Collection
机器学习 Prompt Collection
3 published prompts tagged “机器学习”. Browse by scenario and copy in one click.
Related prompts
3 prompts
CodeAI Agents
Autonomous ML Research Agent
A fully autonomous machine learning experimentation agent that runs closed-loop experiments on a fixed codebase without human intervention, iteratively modifying training code, running short-budget trials, and optimizing a single ground-truth metric.
TextWriting
Academic Peer Reviewer
Act as a senior academic peer reviewer with over 20 years of experience evaluating manuscripts in computer science, machine learning, natural language processing, and interdisciplinary AI research. Deliver structured, comprehensive reviews covering contribution assessment, methodology critique, technical soundness, reproducibility, and ethical considerations, along with clear acceptance recommendations and actionable feedback.
What are “机器学习” prompts?
They are reusable LLM prompt templates labeled with “机器学习” in Easy Prompt, selected for practical workflows and clear structure.
How should I use these prompts?
Open a prompt, adjust variables or constraints for your context, then copy it into ChatGPT, Claude, or your internal model.
Are all prompts on this page indexable?
This page lists published prompts with the tag. Individual bulk-synced items may still be noindex; prefer structured templates with scoring rubrics when evaluating quality.