「ecto」の検索結果

Train ML models on Databricks. Use for: classification/regression/deep-learning (XGBoost, scikit-learn, LightGBM, PyTorch) with Optuna, @prod/@challenger aliases, batch scoring (spark_udf for plain models, fe.score_batch for feature-store-backed), custom PyFunc, custom ResponsesAgent (LangGraph + UC Function/Vector Search); UC feature tables + FeatureLookup + point-in-time joins + Lakebase online store; declarative Feature Views (create_feature, DeltaTableSource, RollingWindow/SlidingWindow/TumblingWindow, materialize_features, streaming Kafka features). NOT for: endpoint ops (databricks-model-serving), MLflow evaluation (databricks-mlflow-evaluation).

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Mine lost deal notes to identify recurring objection patterns. Create objection response playbooks from won deals.

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。

Get a local business found on Google -- audit and optimize the Google Business Profile, local pack ranking factors, review velocity, NAP consistency across directories, and location pages. For businesses whose customers search "near me," this outranks everything else in marketing.

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Uses MCP Connectors to read Gmail inbound leads, score them by ICP fit, draft personalized responses, and log qualified leads to your CRM. Turns your inbox into an automated pipeline.

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Turn a marketing brief or product offer into a finished short-form video ad built in HyperFrames — hook, script, shot-by-shot storyboard, scene-by-scene HTML composition, captions, and voiceover. Outputs platform cuts (vertical 9:16, square, 16:9). Use when you need a launch ad, product promo, social video, or paid-creative concept ready to render.

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Runs small and midsize business bookkeeping operations - categorizes bank and card transactions to a chart of accounts, reconciles a bank or card statement against the ledger, works a month-end close checklist, and produces a close package for the accountant. Works from QuickBooks Online, Xero, bank CSV/OFX, or Mercury exports, and from the Xero, QuickBooks, or Mercury connectors when present. Use it whenever the user says "reconcile", "bank rec", "categorize transactions", "month end close", "close the books", "books don't match the bank", "reconciliation is off by", "uncategorized expenses", or shares a QuickBooks or Xero export or a bank statement CSV, even if they do not name the task. Never plugs a difference; every unreconciled dollar is explained or listed.

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Use when analyzing a researcher's publication record from PubMed. Fetches an author's papers, classifies study types and author position, charts the patterns and writes a strategy report, with an optional trajectory-archetype classification. Works from PubMed metadata only.

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。

Detects AI-generated writing patterns in prose. Use when reviewing docs for slop, vague language, or identity leaks before publishing.

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。

Decides hand-vs-compiler for loop transforms (unrolling, SIMD, fusion, branchless). Use when reviewing/authoring a hot loop or tempted to hand-optimize one.

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。

Detects codebase bloat via dead code, duplication, complexity, and doc bloat scans. Use when codebase feels large or before a release.

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 friction signals; graduate patterns into rules. Use for session retrospectives.

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。

Route GeoAI geospatial data, inference, training, foundation-model, and integration workflows.

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。

Route GenAI Processors tasks to the right workflow guide.

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Use FlagEmbedding for embedding, reranking, retrieval evaluation, and fine-tuning workflows.

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Use face_recognition to detect faces, extract landmarks and encodings, compare identities, run the face_recognition and face_detection CLIs, and troubleshoot dlib/model installation.

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Use face.evoLVe for high-performance face recognition workflows across alignment, data preparation, PyTorch training, feature verification, and Paddle deployment.

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Use ExecuTorch to export PyTorch models to edge runtime artifacts, build host/device runtimes, choose delegates, profile/debug execution, and operate specialized Qualcomm, Cortex-M, LLM, and binary-size workflows.

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Use davidsandberg/facenet for TensorFlow 1.x face recognition workflows: MTCNN alignment, embeddings, classification, LFW evaluation, training, and model export.

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Use this skill for EverOS local-first Markdown memory service setup, HTTP memory and knowledge APIs, cascade/OME operations, and observability integration.

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Router for FunASR speech workflows: local transcription, subtitles, services, vLLM, normalization, and training/export.

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Guide FunClip ASR video/audio clipping, LLM-assisted clipping providers, and release packaging workflows.

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Use Fairlearn to assess group fairness, compute disparity metrics, visualize subgroup performance, and mitigate unfairness with preprocessing, reductions, postprocessing, or adversarial learning.

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Guides Researchers through Faiss installation, dense and binary similarity search, index training and composition, persistence and evaluation, and explicitly gated CPU/GPU interoperability workflows.

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Operate the legacy Frustum PointNets code release for KITTI or SUN RGB-D data preparation, TensorFlow runtime setup, training, inference, and 3D detection evaluation.

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。