'ml' 검색 결과

Review page language attributes so HTML and XML readers receive consistent language information. Check matching lang and xml:lang values, validate language codes, and recommend keeping both attributes for XHTML or removing the unnecessary XML attribute from standard HTML5.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Checking language attributes in XHTML documents
• Removing unnecessary xml:lang attributes from HTML5
• Investigating incorrect screen reader pronunciation

Inspect raw HTML responses for a correct HTML5 doctype at the start of the document. Identify missing or outdated declarations and preceding content, then guide fixes that enable standards-mode rendering in browsers.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Checking the doctype in raw HTML responses
• Replacing old HTML4 or XHTML declarations
• Removing extra content before the doctype

Helps integrate YAML output into json-render, turning incoming text into incremental UI updates. Covers prompt generation, streaming parsing, and targeted edits to existing UI specifications through merge, patch, or diff formats.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Render UI updates as YAML arrives
• Generate prompts for YAML output
• Apply partial edits to existing UI specifications

발표 메모나 PowerPoint로 브라우저에서 실행되는 HTML 슬라이드를 만듭니다. 미리보기로 디자인을 선택하고 화면에 맞는 레이아웃과 애니메이션을 구성합니다.

• 발표와 사내 보고용 슬라이드를 만듭니다
• PowerPoint를 HTML로 변환합니다
• 미리보기로 자료 디자인을 선택합니다

Find and fix malformed HTML, including unclosed tags, incorrect nesting, and document structure errors. Inspect rendered HTML and HTTP responses to identify specific pages or templates with problems that may affect rendering and search engine parsing.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Finding unclosed tags and incorrect nesting
• Investigating HTML-related rendering problems
• Checking HTML structure for search engine parsing

Turn completed research, analysis, reports, or plans from the current session into a self-contained HTML artifact. A renderer controls layout, typography, and color, using structured content and a choice of two visual styles.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Turn research findings into an HTML artifact
• Format a cost analysis with tables and callouts
• Present investigation findings as a designed document

Compare a PPTX exported from HTML with its source slides to find cropped text, footer overlaps, and lost styling. Identify shared causes, revise layout rules, and re-export the deck with automated checks for content extending beyond slide boundaries.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Check an HTML slide deck against its exported PPTX
• Fix cropped text and footer overlaps
• Investigate missing italics and unexpected fonts

Convert Markdown files into styled HTML suitable for WeChat and other platforms. Choose themes, colors, and fonts, preserve code and diagrams, and optionally turn external links into numbered references at the end.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Converting Markdown articles into styled HTML
• Formatting articles for WeChat
• Exporting documents containing code and diagrams

Classical end-to-end empirical analysis workflow in the traditional Python econometric stack — pandas + numpy + scipy + statsmodels + linearmodels + pyfixest + rdrobust + econml + causalml + matplotlib/seaborn. **Defaults to economics empirical-paper style** (AER / QJE / AEJ) — every run produces a publication-ready output set with a multi-column regression table (M1→M6 progressive controls/FE) as the centerpiece, plus Table 1 (descriptives), mechanism / heterogeneity / robustness tables, and event-study + coefficient + trend figures. Covers the full 8-step pipeline an applied economist or quantitative social scientist runs on every paper — (1) data cleaning, (2) variable construction & transformation, (3) descriptive statistics & Table 1, (4) statistical diagnostic tests, (5) baseline empirical modeling, (6) robustness battery, (7) further analysis (mechanism, heterogeneity, mediation, moderation), (8) publication-ready tables & figures. **Also covers two parallel domain modes that share the same 8-step scaffolding** — **Mode A — Epidemiology / public health** (target-trial emulation via `zepid` / hand-rolled `pandas`, IPTW + g-formula + TMLE doubly-robust triplet via `zepid` / `econml` / `lifelines`, Mendelian randomization via `pymr` / `mrtool` (or `rpy2` → `MendelianRandomization`/`TwoSampleMR`), KM / AFT / Cox survival via `lifelines`, E-value sensitivity, principal stratification — STROBE / TRIPOD reporting), and **Mode B — ML causal inference** (DML via `econml.dml` / `doubleml`, S/T/X/R/DR meta-learners via `econml.metalearners` / `causalml`, causal forest via `econml.grf` / `causalml`, Dragonnet / TARNet / CEVAE neural causal via `causalml`, BCF via `pymc-bart` / `bcf-py`, matrix completion, CATE distribution + policy tree via `econml.policy` / `policytree-py`, off-policy evaluation, conformal causal via `mapie`, fairness audit via `fairlearn`, DAG learning via `causal-learn` / `cdt` / LLM-assisted). Prescribes which library to reach for at each step, shows the canonical code, and links to deeper `references/` files for variant-specific patterns. Use when the user asks for a **complete empirical analysis** in Python, wants to replicate an applied-economics paper from scratch, needs a reproducible workflow that is NOT opinionated on any single vertical package (contrast with StatsPAI), wants explicit control over every estimator and diagnostic, or asks "how do I write a full empirical pipeline in Python?". Also triggers when the user names a specific classical step in isolation — "winsorize at 1/99%", "run Breusch-Pagan", "build a Table 1 balance table", "do a placebo test", "event study plot", "mediation analysis" — and wants it wired into the broader pipeline. Mode A triggers on "target trial emulation", "IPTW", "TMLE", "Mendelian randomization", "STROBE", "公共健康", "流行病学". Mode B triggers on "DML", "double machine learning", "causal forest", "meta-learner", "Dragonnet", "BCF", "policy tree", "conformal causal", "fairness audit", "因果机器学习".

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

Review HTML pages, presentations, or prototypes across five design dimensions. Receive evidence-backed scores, a radar chart, and practical lists of what to keep, fix, or improve quickly, all packaged in a single self-contained HTML report.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Reviewing a landing page before delivery
• Checking the readability and navigation of an HTML presentation
• Comparing two versions of a design

Review rendered HTML and replace generic div elements with elements that describe their purpose, such as main, nav, and article. Clarify page structure to support screen-reader navigation, search-engine understanding, and code maintenance.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Reviewing page structure built mostly with div elements
• Checking HTML output from templates and shared components
• Improving page structure for screen-reader navigation

Audit HTML page size and identify oversized embedded JSON, SVGs, images, or scripts. Use the findings to plan lighter pages and investigate whether document size could explain content missing from Google's search index.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Investigating content missing from Google's index
• Reviewing large JSON payloads embedded in HTML
• Checking HTML size across an e-commerce site

Review HTML for deprecated ARIA roles, which describe elements to assistive technology, and abstract roles that should not appear in markup. Suggest recommended replacements or native HTML elements and explain potential browser and screen reader compatibility issues.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Find deprecated ARIA roles in existing code
• Review whether native HTML can replace custom roles
• Inspect role usage in shared UI components

Convert Markdown documents into HTML for web pages, documentation, or previews. Covers single files, batch conversion, and static site workflows, with guidance on tables, code blocks, math rendering, and handling untrusted content safely.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Convert Markdown documentation into HTML
• Batch-convert multiple .md files
• Build static sites from Markdown

Develop and troubleshoot Apache Beam's YAML SDK. Understand its source files, run data processing pipelines locally or on Dataflow, test changes, and investigate provider issues or mismatched record fields.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Find source files for Beam YAML changes
• Run a YAML pipeline locally or on Dataflow
• Run unit tests and external service integration tests

Turn long Markdown files into a single HTML file for reading, reviewing code, or presenting slides. Routes each input to a specialized converter and applies shared design settings, with navigation and interaction suited to the document type.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Converting long specifications or reports into navigable HTML
• Presenting code reviews with diffs and severity annotations
• Turning Markdown into slides with keyboard navigation

Use MLflow to record machine learning experiments, compare results, and manage model versions. The skill covers logging training settings, metrics, and files, organizing a model registry, and preparing models for local or cloud deployment.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Comparing training settings and model performance
• Recording experiments for later reproduction
• Managing model versions and release stages

Set shared brand colors, fonts, layout style, and table of contents behavior for markdown-html outputs. A guided setup checks text and link contrast, derives twelve reusable CSS settings, and saves preferences globally or per project.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Setting a shared style for HTML documents and slides
• Checking text and link color contrast
• Saving a separate brand style for a project

Check XML sitemaps for format errors, problematic URLs, inaccurate modification dates, and missing pages. Generate new sitemaps using industry templates, with file splitting where needed and documentation of the planned site structure.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Checking existing sitemaps for errors and fixes
• Generating an XML sitemap for a new site
• Splitting large sitemaps and creating an index

Generate FrontendIntegration YAML for frontend-forge from a simplified configuration containing one menu and one or more pages. Define resource tables or embedded iframe pages, with the bundled generator expanding menu placements into the required YAML structure.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Generating integration YAML for a CRD resource table
• Defining an embedded iframe page
• Converting a single-menu configuration into canonical YAML

Choose, create, and review software diagrams that explain structure, interactions, workflows, states, or data relationships. Select suitable notation and rendering tools, then plan static exports or interactive views with readable layouts, accessible controls, and validation.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Explain login interactions with a sequence diagram
• Turn a database schema into an entity relationship diagram
• Document application architecture with C4

Add compact visual summaries to Markdown answers using static HTML and CSS. Show comparisons, key metrics, timelines, or simple relationships in a preview, while keeping explanations and detailed information in the surrounding text.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Comparing key metrics visually
• Showing a process or sequence of steps
• Summarizing events on a timeline

Build complex interactive artifacts for claude.ai with React, Tailwind CSS, and shadcn/ui. Start from a configured project, develop interfaces with state management or navigation, and bundle the result into one shareable HTML file.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Building interactive interfaces with multiple components
• Creating artifacts with state management and navigation
• Developing interfaces with shadcn/ui components

Create text diagrams with PlantUML for README files, emails, and terminal workflows. Convert diagram definitions into plain ASCII or Unicode box-drawing output to share interactions and relationships where image-based diagrams are unsuitable.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Add text diagrams to README files
• Share sequence diagrams in emails
• View diagrams in a terminal