「network」の検索結果

Supervised and unsupervised learning, bias-variance tradeoff, cross-validation, decision trees, ensemble methods, neural network fundamentals, and the practitioner's workflow from problem framing through deployment. Covers classification, regression, clustering, dimensionality reduction, regularization, hyperparameter tuning, and evaluation metrics. Use when building predictive models, selecting algorithms, or understanding the machine learning pipeline.

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Entrepreneurship, innovation, and disruption for starting, scaling, and defending new ventures. Covers opportunity recognition, jobs-to-be-done, the disruptive innovation framework, sustaining vs disruptive innovation, platform businesses, network effects, minimum viable product, customer development, and the startup lifecycle from idea to exit. Use when evaluating a venture idea, positioning a new product, interpreting a competitive threat, or designing a platform.

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OpenStack capacity planning operations skill for resource planning, quota management, and scaling decisions. Covers compute capacity (allocation ratios, vCPU/RAM utilization, host aggregates, availability zones), storage capacity (Cinder pool sizing, thin provisioning, Glance storage, Swift rings), network capacity (floating IP pools, port quotas, subnet sizing), project quota management (templates for small/medium/large profiles), flavor sizing strategy, utilization analysis with placement service, growth forecasting from historical metrics, and right-sizing recommendations for underutilized resources.

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OpenStack security operations skill for hardening, certificate management, and security posture assessment of cloud infrastructure. Covers TLS certificate lifecycle (generation, deployment, rotation, expiry monitoring), security group management (default deny, minimum required openings), RBAC policy customization (per-service policy.yaml), network segmentation (management vs tenant vs external), audit logging (Keystone CADF events), vulnerability assessment procedures, compliance auditing, intrusion detection patterns, incident response procedures (credential compromise, instance compromise), password rotation, and API rate limiting. Use when hardening OpenStack, managing certificates, auditing security posture, or responding to security incidents.

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Zephyr RTOS development — boards and devicetree, the build system (west, Kconfig, CMake, sysbuild), drivers and peripherals, BLE and networking, the kernel, storage, power, testing and debugging, security and OTA. Use this for ANY Zephyr RTOS or embedded-firmware task on a Zephyr project; it routes you to the right specialized skill via the zephyr-cli registry.

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Scholze-Clausen condensed mathematics bridge to sheaf neural networks via 6-functor formalism

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Condensed ANIMA on quantum-classical and classical-quantum networks. All skill compositions materialized as s-expressions across the polyglot substrate.

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Bridge layer connecting AlgebraicJulia/Catlab.jl to plurigrid/asi. Wires ACSets (attributed C-sets), wiring diagrams, decorated cospans, and the AlgebraicJulia ecosystem (AlgebraicDynamics, AlgebraicPetri, AlgebraicRewriting, Decapodes) into the ASI skill graph. ACSets generalize relational databases with categorical semantics; every diagram, network, and model in the ecosystem is an ACSet.

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Comprehensive Cloudflare platform skill covering Workers, Pages, storage (KV, D1, R2), AI (Workers AI, Vectorize, Agents SDK), networking (Tunnel, Spectrum), security (WAF, DDoS), and infrastructure-as-code (Terraform, Pulumi). Use for any Cloudflare development task.

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Automate browser interactions for web testing, form filling, screenshots, and data extraction. Use when the user needs to: - Navigate websites and interact with web pages - Fill forms and click buttons - Take screenshots of web content - Test web applications - Extract information from web pages - Debug frontend issues in the browser - Monitor console logs and network requests - Record browser sessions as video This skill uses agent-browser for comprehensive browser automation. RECOMMENDATION: Disable Chrome DevTools or Playwright MCP when using this skill to save context.

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Chemical reaction network modeling with Catalyst.jl. Autopoietic systems, unit-aware ODEs, and interacting subsystems.

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CatColab Petri Nets - concurrent system modeling via places (states), transitions (events), and token flow. Foundation for process algebra, workflow, and chemical reaction networks.

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Unified messaging via Beeper Desktop MCP. Search chats, send messages, manage conversations across all networks (iMessage, WhatsApp, Signal, Telegram, Discord, Slack, etc.)

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Infer gene regulatory networks (GRNs) from gene expression data using scalable algorithms (GRNBoost2, GENIE3). Use when analyzing transcriptomics data (bulk RNA-seq, single-cell RNA-seq) to identify transcription factor-target gene relationships and regulatory interactions. Supports distributed computation for large-scale datasets.

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Unified messaging via three access tiers — MCP (live API), beeper-cli (authenticated CLI), and direct SQLite→DuckDB (full archive). Search, analyze, and act across all networks.

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Artificial Life atlas covering open-ended evolution, chemical reaction networks, morphogenesis, self-replication, and programmable chemistry. Use when picking a simulation framework, wiring ALife models into the skill graph, or onboarding contributors to the ALife cluster.

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ALIFE 2025 Proceedings - 337 pages, 80+ papers on artificial life, evolution, emergence, cellular automata, neural networks, agent-based models. Full Mathpix extraction with equations and figures.

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Search academic papers across arXiv, PubMed, Semantic Scholar, bioRxiv, medRxiv, Google Scholar, and more. Get BibTeX citations, download PDFs, analyze citation networks. Use for literature reviews, finding papers, and academic research.

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Formal oracle for abductive inference that selects the minimal hypothesis best explaining a set of observations. Provides three sub-oracles: MCMC via monad-bayes, Gemini for natural language, and propagator networks for constraint domains. Use when performing hypothesis selection, explaining observations, or solving inference-to-best-explanation problems.

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Manage Alibaba Cloud Elastic Compute Service (ECS) using the @alicloud/ecs20140526 TypeScript SDK. Use when working with cloud servers on Alibaba Cloud, including instance lifecycle (create, start, stop, reboot, delete), disks and snapshots, images, security groups, VPC networking, EIP, ENI, SSH key pairs, dedicated hosts, auto provisioning, launch templates, Cloud Assistant commands, tags, system events, diagnostics, storage capacity units, and prefix lists. Covers all 374 APIs of the ECS 20140526 version.

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。

Protocol-based dependency injection for testable Swift code — mock file system, network, and external APIs using focused protocols and Swift Testing.

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。

Docker and Docker Compose patterns for local development, container security, networking, volume strategies, and multi-service orchestration.

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Designs publication figures for social-science manuscripts. Covers chart choice, axes and scales, color and accessibility, legend order, captions that carry the title, and script-based reproducibility. Use when making, revising, or critiquing a figure for a paper, such as a coefficient plot, small multiples, a distribution, a trend, a map, or a network. Finished figure sets go to figure-table-audit for end-stage QA.

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。

Self-evolution workflow for the agent. Before substantive work, recall past outcomes from evolution memory; while editing, detect improvement signals; at task end, record the outcome; when reusable, distill or search the EvoMap network for proven genes/capsules. Use when the user starts non-trivial work (a feature, a fix, a refactor) or asks the agent to "evolve", "learn from this", or "remember how this went".

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。