interview-cheatsheet

Generate Chinese ML/LLM interview cheat sheets with formulas, PyTorch code, and tiered questions.

2|Updated Aug 12, 2025
One-click install
npx skills add https://github.com/goupup-ai/miccai25 --skill interview-cheatsheet-goupup-ai
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: interview-cheatsheet
Source: https://github.com/goupup-ai/miccai25/tree/main/ARIS/skills/interview-cheatsheet
Command: npx skills add https://github.com/goupup-ai/miccai25 --skill interview-cheatsheet-goupup-ai

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

Preparing for ML/LLM technical interviews in Chinese requires manually compiling formula derivations, implementation code, comparison tables, and common interview questions, which is time-consuming and often misses key high-frequency test points.

Core Features & Use Cases

  • Comprehensive Cheat Sheet Generation: Produces 600-1000 line Chinese tutorials covering formula derivations, from-scratch PyTorch code, variant comparisons, and 25 tiered high-frequency interview questions (L1 basic, L2 advanced, L3 top lab level).
  • Cross-Validated Accuracy: Runs automated math, code, and factual correctness reviews via external models to ensure all content is accurate and executable.
  • Use Case: ML/LLM algorithm interview candidates can use this skill to generate a complete, review-ready cheat sheet for niche topics like RLHF, MoE, or Speculative Decoding in minutes, instead of spending hours collating scattered resources.

Quick Start

Use the interview-cheatsheet skill to generate a full Chinese interview prep cheat sheet with formulas, code, and 25 high-frequency questions for your target ML/LLM topic.

Frequently Asked Questions about interview-cheatsheet

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
How do I generate a Chinese ML interview cheat sheet with formula derivations and PyTorch code?▼

To generate a Chinese ML interview cheat sheet, specify your target topic like RLHF or MoE, and the skill outputs a 600-1000 line tutorial containing formula derivations, from-scratch PyTorch code, and tiered interview questions.

What is the best way to prepare for LLM algorithm interview questions on niche topics like KV Cache?▼

The best way to prepare for LLM algorithm interviews on niche topics like KV Cache is generating a structured cheat sheet that provides variant comparisons, mathematical derivations, and 25 tiered high-frequency interview questions.

Does the generated interview prep material include from-scratch implementation code for distributed training?▼

Yes, the generated interview prep material includes from-scratch PyTorch implementation code for topics like distributed training, ensuring the content is executable and cross-validated for correctness.

Can I get tiered LLM interview questions ranging from basic to top lab level?▼

Yes, you can get tiered LLM interview questions categorized into L1 basic, L2 advanced, and L3 top lab level, providing a comprehensive review set for machine learning and large language model roles.

How accurate are the mathematical derivations in automated ML interview preparation materials?▼

The mathematical derivations in automated ML interview preparation materials are highly accurate, utilizing external models to run automated math, code, and factual correctness reviews for cross-validated reliability.