Results for “mdl”

Machine learning development agent for end-to-end ML workflows: data preprocessing, model training, evaluation, hyperparameter tuning, and deployment

Provides practical guidance for training Mixture-of-Experts Vision-Language Models in Megatron Bridge, comparing FSDP and 3D-parallel approaches with lessons from recent multimodal experiments.

Run Megatron-LM (MLM) and Megatron Bridge training with mock or real data, covering correlation testing, available recipes, and multi-GPU examples.

Guides the creation of high-quality MCP servers that enable LLMs to interact with external services through well-designed tools, covering planning, implementation, testing, and evaluation.

Kernel-Mode Driver Framework (KMDF), the Microsoft-recommended way to write Windows kernel-mode drivers. Covers DriverEntry, EvtDeviceAdd, IRPs and IOCTLs, I/O queues, PnP and Power state machines, IRQL discipline, memory pools, WPP tracing, SAL annotations, and Driver Verifier. USE WHEN: user mentions "KMDF", "WDF kernel", "Windows kernel driver", "DriverEntry", "WdfDriverCreate", "EvtDeviceAdd", "IRP", "IOCTL", "DISPATCH_LEVEL", "PASSIVE_LEVEL", "NTSTATUS", "PoolTag", "WdfRequestComplete" DO NOT USE FOR: UMDF v2 (use `wdf-umdf`), classic WDM-only drivers, file-system filters (FltMgr is a separate framework)

Guides machine learning development with experiment tracking, hyperparameter optimization, model registry, and MLOps pipeline integration.

Build production ML systems with PyTorch 2.x, TensorFlow, and modern ML frameworks, including model serving, feature engineering, A/B testing, and monitoring.

ML pipeline design — data versioning, experiment tracking, deployment patterns, drift monitoring. Use when building an ML pipeline from data to deployment, setting up MLOps tooling (DVC, MLflow, model registry), choosing deployment patterns (shadow, canary, A/B), or designing monitoring for drift and degradation.

Designs and implements production-grade ML pipeline infrastructure: configures experiment tracking, creates orchestration DAGs, builds feature store schemas, deploys model registries, and automates retraining and validation workflows.

Classify medical devices under EU MDR 2017/745, build technical documentation, plan clinical evaluations, and manage post-market surveillance and EUDAMED integration.

Converts a markdown deck into a single-file HTML presentation with keyboard navigation, presenter mode, and print-to-PDF support.

Guide for creating high-quality MCP (Model Context Protocol) servers that enable LLMs to interact with external services through well-designed tools. Use when building MCP servers to integrate exte...

Agent skill for data-ml-model - invoke with $agent-data-ml-model

Use this skill when a driver holds CDLs in multiple states or has resided in multiple states. Covers what MVRs to pull, federal recordkeeping requirements, and state-specific issues.

Guides the creation of MCP servers that enable LLMs to interact with external services through well-designed tools.

Build production ML systems with PyTorch 2.x, TensorFlow, and modern ML frameworks. Implements model serving, feature engineering, A/B testing, and monitoring.

ML Pipeline Specialist IA — Expert en pipelines ML (feature stores, data versioning, experiment tracking, model registry)

Build production ML systems with PyTorch 2.x, TensorFlow, and modern ML frameworks. Implements model serving, feature engineering, A/B testing, and monitoring.

Direct TMDL file authoring and BIM-to-TMDL conversion for semantic models in PBIP projects. Automatically invoke when the user asks to "edit TMDL", "add a measure in TMDL", "TMDL syntax", "fix formatString", "fix summarizeBy", "TMDL indentation", "convert BIM to TMDL", "add a column description", "create a calculated column in TMDL", or mentions .tmdl file editing or BIM-to-TMDL migration.

Registers an AI agent identity, sets a 3D avatar, lists spaces, and joins a space in the Doppel virtual world via headless API calls.

Guides the creation of high-quality MCP servers that enable LLMs to interact with external services through well-designed tools, covering planning, implementation, testing, and evaluation across multiple programming languages.

Choose between DML statements and Database class methods for bulk Salesforce operations, handling partial success, DMLOptions, and error collection.

Guide for creating high-quality MCP (Model Context Protocol) servers that enable LLMs to interact with external services through well-designed tools. Use when building MCP servers to integrate external APIs or services, whether in Python (FastMCP) or Node/TypeScript (MCP SDK).

Guides the creation of high-quality MCP servers that let LLMs interact with external services through well-designed tools, covering planning, implementation, testing, and evaluation.

Converts long-form markdown documents (specs, RFCs, reports, plans) into a single-file HTML page with sticky table of contents, scrollspy, search filter, code-copy buttons, and customizable design tokens.

Executa consultas, inspeção de schema e mutações seguras (DML/DDL com dry-run) no PostgreSQL via servidor MCP, exigindo confirmação explícita para alterações.

Debugs ML pipelines by identifying data leakage, overfitting, and distribution shift issues

Enforces ML infrastructure, experiment tracking, reproducibility, model packaging, CI/CD, monitoring, and infrastructure-as-code standards at principal-engineer level.

Comprehensive guide to mdp. Master the concepts, implementation, best practices, and real-world applications of mdp in professional environments.

Guide for creating high-quality MCP (Model Context Protocol) servers that enable LLMs to interact with external services through well-designed tools. Use when building MCP servers to integrate external APIs or services, whether in Python (FastMCP) or Node/TypeScript (MCP SDK).

生产级机器学习工程工作流——数据契约、可复现训练、模型评估、服务部署、监控与回滚

Use when implementing ML functionality with production-grade patterns and safeguards.

Documents MariaDB-specific ALTER TABLE syntax and behavior, including online DDL algorithms, lock modes, lock timeouts, idempotent subclauses, system versioning, and partition operations, for writing and reviewing schema migrations.

Guide for creating high-quality MCP (Model Context Protocol) servers that enable LLMs to interact with external services through well-designed tools. Use when building MCP servers to integrate external APIs or services, whether in Python (FastMCP) or Node/TypeScript (MCP SDK).

Run and analyze molecular dynamics simulations with OpenMM and MDAnalysis. Set up protein/small molecule systems, define force fields, run energy minimization and production MD, analyze trajectories (RMSD, RMSF, contact maps, free energy surfaces).