「ml」の検索結果

Create and edit draw.io/diagrams.net diagrams as editable `.drawio` files. Covers architecture, UML/ERD/sequence, BPMN, network, and swimlane views authored from a description or converted from code, IaC, SQL, and API schemas, plus sync, query, test, review, export, and publish of existing diagrams. Use when the user asks for draw.io/diagrams.net or an editable diagram; prefer Mermaid/PlantUML when diagrams-as-code is enough.

日本語の概要は準備中です。原文の説明を表示しています。

Drafts board-ready Anti-Money Laundering compliance programs for U.S. financial institutions under BSA/FinCEN requirements. Covers CIP, CDD, EDD, SAR/CTR reporting, OFAC screening, risk assessment, training, independent testing, and governance structures. Use when creating or updating AML policies, BSA compliance programs, or financial institution regulatory documentation. Trigger keywords: AML, BSA, FinCEN, Bank Secrecy Act, anti-money laundering, SAR, CTR, OFAC, CIP, CDD, KYC, compliance program.

日本語の概要は準備中です。原文の説明を表示しています。

Render a wiki into ONE self-contained HTML snapshot (pages + provenance) that opens offline — no CDN, no remote assets, page content HTML-escaped. Use to share or review accumulated wiki knowledge as a static page. NOT for capturing/approving knowledge (see mk:wiki); NOT for generic code/diagram visuals (see mk:preview).

日本語の概要は準備中です。原文の説明を表示しています。

Add CSS animations to HTML elements, React/JSX components, or WordPress PHP templates using Animate.css (v4.1.1). Use this skill whenever the user wants to animate UI elements, add entrance/exit effects, attention-seeker animations, or any CSS-based motion to their markup. Trigger on phrases like "add animation", "animate this", "make it bounce/fade/slide/zoom", "add transitions", "CSS animations", or any request to bring elements to life visually. Works with raw HTML snippets, full HTML files, React JSX, and WordPress PHP templates. Claude picks the most contextually appropriate animation — no guesswork needed from the user.

日本語の概要は準備中です。原文の説明を表示しています。

Build interactive HTML/web visualizations with plotly (Python/R), bokeh (Python), and gganimate/plotly frames for animation, with awareness of current Kaleido static-export model (post-orca-EOL), HTML file-size bloat, and the limits of interactive-only output for journal submission. Use when producing zoomable/hoverable plots for notebook EDA, supplementary HTML, dashboards, or animated time-course / iteration visualizations.

日本語の概要は準備中です。原文の説明を表示しています。

Detect positive (diversifying / episodic / pervasive) selection using codon dN/dS frameworks. Implements PAML codeml site models (M0/M1a/M2a/M7/M8/M8a), branch models, branch-site model A (Zhang 2005), and HyPhy methods (BUSTED, BUSTED-S, BUSTED-MH, BUSTED-PH, MEME, FEL, FUBAR, aBSREL, SLAC, RELAX, GARD, FUBAR-MH). Includes McDonald-Kreitman framework (asymptotic alpha, impMKT, polyDFE, DFE-alpha, GRAPES) for within-species + divergence inference, RERconverge for trait-correlated rate shifts, CSUBST for convergent substitution, and PhyloAcc for accelerated noncoding evolution. Use when testing adaptive evolution at codons, branches, or full gene; running GARD recombination pre-screen; controlling alignment-error and gBGC false positives; reconciling PAML vs HyPhy results; or performing genome-scale selection scans.

日本語の概要は準備中です。原文の説明を表示しています。

Reconstruct ancestral states at internal phylogenetic nodes for sequences (PAML codeml, IQ-TREE --ancestral, GRASP, FastML), discrete traits (corHMM hidden-rate Markov, ape::ace, phytools::make.simmap stochastic mapping, BayesTraits), and continuous traits (phytools::fastAnc, geiger Brownian/OU, RPANDA). Use when designing constructs for ancestral protein resurrection, tracing trait evolution along a tree, performing stochastic character mapping, testing models of trait evolution (BM vs OU vs EB), inferring ancestral genome content via Dollo or DTL reconciliation, or quantifying ancestral-state uncertainty for downstream comparative analyses.

日本語の概要は準備中です。原文の説明を表示しています。

Estimates SNP heritability and partitions it across functional annotations, cell types, and loci from GWAS summary statistics or individual-level genotypes. Implements LDSC, stratified LDSC with the baseline-LD model, Finucane 2018 cell-type prioritization, LDAK SumHer, HDL, HESS local heritability, BOLT-REML, GCTA-GREML, graphREML, and Popcorn cross-population genetic correlation. Use when computing total h2_SNP from summary stats, partitioning heritability across functional categories, prioritizing trait-relevant tissues or cell types from ENCODE/Roadmap chromatin marks, reconciling LDSC vs LDAK enrichment estimates, computing local heritability with HESS, estimating genetic correlation between traits, or producing publication-grade enrichment with calibrated sensitivity to model assumptions.

日本語の概要は準備中です。原文の説明を表示しています。

Determines if primary aldosteronism is confirmed based on upright plasma aldosterone ≤6 ng/dL (170 nmol/L) on day 4 at 10 AM of fludrocortisone suppression test, provided plasma renin activity ≥1 ng/mL/h and plasma cortisol concentration lower than the 7 AM value to exclude ACTH confounding. Use when reviewing FST results to diagnose PA; triggers include "FST", "upright aldosterone ≤6 ng/dL", "PRA ≥1 ng/mL/h", and "cortisol drop".

日本語の概要は準備中です。原文の説明を表示しています。

Isolate the root cause of ML performance drops, inconsistent evaluations, prediction errors, and training-serving mismatches across data, labels, splits, pipelines, models, metrics, and runtime behavior. Use when investigating a reproducible failure or regression, not routine model selection or general performance validation.

日本語の概要は準備中です。原文の説明を表示しています。

Post-train LLMs with PrimeIntellect's prime-rl (async RL, SFT, distillation, evals). Use this skill whenever the user mentions prime-rl, wants to write an rl.toml or sft.toml, run `uv run rl` / `uv run sft` / `uv run eval` / `uv run inference`, pick GRPO, MaxRL, OPD or ECHO, tune IPO loss, or monitor and resume a run. Also trigger for verifiers environments, Prime Intellect post-training, reverse-text, and pydantic-config TOML overrides.

日本語の概要は準備中です。原文の説明を表示しています。

Build GenAI and agentic apps with genai-tk (tclatos/genai-tk), a YAML-driven IoC toolkit over LangChain, DeepAgents, DeerFlow, and Prefect. Use this skill whenever the user mentions genai-tk, genai_tk, `cli init`, `cli agents run`, `LangchainAgent`, `create_harness`, `get_llm`, `global_config()`, `model_id@provider`, `agents:`/`agent_defaults:` profiles, `RetrieverFactory`, `cli workflow`, or BAML extraction. Also trigger for app_conf.yaml, GENAITK_PROFILE, CodeAct, OpenSandbox, decision models, or "the toolkit".

日本語の概要は準備中です。原文の説明を表示しています。

Use this skill whenever the user wants to create, edit, explain, validate, or troubleshoot a proctmux.yaml/procmux.yaml file, add or change proctmux processes, configure lifecycle behavior such as stop signals/on_kill/autostart, customize unified-mode layout/keybindings/style, or enable Makefile/package.json process discovery. Use it even when the user says this casually, such as "add my dev server to proctmux", "fix this proctmux config", "write a config for these services", or "what YAML option controls focus".

日本語の概要は準備中です。原文の説明を表示しています。

Escreva papers prontos para publicação em NeurIPS, ICML, ICLR, ACL, AAAI, COLM. Use quando estiver elaborando papers a partir de repositórios de pesquisa, estruturando argumentos, verificando citações ou preparando submissões finais. Inclui templates LaTeX, diretrizes de revisores e workflows de verificação de citações.

日本語の概要は準備中です。原文の説明を表示しています。

Construa sistemas de ML em produção com PyTorch 2.x, TensorFlow e frameworks modernos de ML. Implementa model serving, feature engineering, A/B testing e monitoramento.

日本語の概要は準備中です。原文の説明を表示しています。

Rastreie experimentos de ML com logging automático, visualize treinamento em tempo real, otimize hiperparâmetros com sweeps e gerencie registro de modelos com W&B - plataforma colaborativa de MLOps

日本語の概要は準備中です。原文の説明を表示しています。

可变体的 warm editorial 演示设计系统，用于 presentation、case sharing、项目汇报、战略叙事和产品发布。支持横向全屏 HTML deck 与程序化 PPTX，通过 style profile、语义 slide manifest、构图新颖度规划和反重复验证，在保持编辑设计 DNA 的同时避免固定配色、固定卡片和固定 11 页模板。用户要求 Pfizer/Anthropic/warm editorial/编辑设计风格、类似血液科那套，或需要高规格且非模板化的 HTML/PPT 演示时使用。

日本語の概要は準備中です。原文の説明を表示しています。

将Markdown文章转换为美化的HTML格式，适配微信公众号发布。应用专业CSS样式、代码高亮、优化排版。当用户说"美化这篇文章"、"转换为HTML"、"优化公众号格式"、"生成公众号HTML"时使用。

日本語の概要は準備中です。原文の説明を表示しています。

GStack design-html method for producing or planning quick HTML prototypes, design boards, or rendered visual explorations for UI review.

日本語の概要は準備中です。原文の説明を表示しています。

YAML仕様が変わったか確認するとき、公式仕様との差分を確認するときに使う。

Distributed machine learning, data mining, and iterative HPC with Exasol. Covers end-to-end ML pipelines (DISTRIBUTE BY + SET scripts + BucketFS), per-entity federated training with partial_fit and ctx.reset(), batch inference, map-reduce ensemble training, distributed ensemble and SON algorithm for frequent itemset mining (Apriori, FP-Growth, association rules, market-basket analysis), Lua execute script orchestration for iterative algorithms (k-means, SGD, gradient descent), scikit-learn model training, parallel hyperparameter search, per-entity forecasting, anomaly detection, model lifecycle in BucketFS (pickle/joblib/ONNX versioning), GPU acceleration via CUDA SLCs (PyTorch/TensorFlow/RAPIDS), and ML-specific performance tuning (skew, OOM, multi-pass chunking).

日本語の概要は準備中です。原文の説明を表示しています。

HTML-first persistent planning skill. Generates a single self-contained plan.html with interactive phases, drag-and-drop tickets, sliders, mockups, and embedded JSON state. Survives /clear via session catchup, tamper-protected by SHA-256, mirrors across 17 IDEs, ships 10 templates across Thariq's 9 categories, exports back to Markdown on demand. Use when asked to "plan it", "make me an html plan", "show me the plan", "render the plan", or when starting any multi-step task that needs a navigable artifact instead of a markdown wall.

日本語の概要は準備中です。原文の説明を表示しています。

Export Codex rollout/session JSONL as a self-contained HTML report that can be opened offline. Use when a user provides a complete session file path or Codex session ID, or asks to export a Codex session to HTML, generate a session report, or convert a rollout to HTML. Supports exact full-ID lookup in the CODEX_HOME sessions and archived_sessions directories.

日本語の概要は準備中です。原文の説明を表示しています。

Signpost (not a knowledge pack) for OMG modelling specifications — UML, SysML, BPMN, UAF, SoaML, MOF, OCL, XMI, DDS. Contains NO source content: it only points to where the official specs live and what each is for. Use when you need an OMG modelling/architecture specification — the OMG licence forbids redistributing or transforming the text, so these cannot be reconstituted into a pack; download them from OMG directly.

日本語の概要は準備中です。原文の説明を表示しています。