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SHAP Model Explainability
shap
K-Dense-AI/claude-scientific-skills
318
Guides using SHAP to explain ML predictions, compute feature importance, generate diagnostic plots, debug models, analyze bias, and compare models across tree, deep, linear, or black-box architectures.
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Prioritizing Movie Clues for Search
movie-distinctive-clue
EverMind-AI/EverOS
292
This technique guides users on how to construct highly effective search queries for movies. When a movie question contains both general plot descriptions and highly specific details (such as exact quotes, precise rating language, or specific award names), the user must prioritize the most discriminative clue. By focusing on unique identifiers, this method significantly improves the accuracy and efficiency of information retrieval.
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Guidelines for Theoretical ML Numerics
colt-experiments
brycewang-stanford/Awesome-Journal-Skills
84
A detailed guide for authors submitting theoretical machine learning papers (like COLT) regarding the appropriate inclusion and design of numerical simulations. It emphasizes that numerics should only visualize proved bounds, phase transitions, or separations, maintaining the focus on theoretical proofs rather than empirical data. Provides rules for plotting, reporting variability, and maintaining academic honesty.
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Liu Cixin Sci-Fi Thinking
liucixin-perspective
momozi1996/awesome-ai-persona-skills
366
Emulates Liu Cixin's hard science fiction creative thinking, offering frameworks for macro-detail narrative, scientific concept-driven social conflict, technological optimism, and cosmic sociology. Ideal for generating sci-fi story ideas, worldbuilding, and dark forest-style plot conflicts.
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简体中文
English