Results for “tracking”

Trains, evaluates, exports, quantizes, and runs inference for Sparse4D multi-camera temporal 3D object detection and tracking models using TAO.

Deploy an entire redesigned site to AEM Edge Delivery Services by inventorying migrated pages, deduplicating blocks, and driving per-page deployment with tracking and verification.

Scans a codebase for security vulnerabilities using CodeQL's interprocedural data flow and taint tracking analysis, with support for multiple languages, scan modes, and data extension models.

Manage Weights & Biases ML experiment tracking instances on Azure using the .NET SDK. Create, configure, list, update, and delete W&B instances with marketplace integration and SSO.

Track and visualize ML training experiments with Trackio, including logging metrics, firing alerts, and retrieving data via CLI. Supports real-time dashboards, webhook alerts, and HF Space syncing.

Create, update, and manage GitHub issues using MCP tools and the GitHub CLI.

Identify missing features in a project, prioritize them, and create detailed GitHub issues with specifications.

Creates a GitHub issue from a specification file using a feature request template, checking for existing issues first.

Manage issues, projects, and team workflows in Linear using the Linear MCP server for natural-language project management.

Get best practices for Entity Framework Core, covering data context design, entity design, performance, migrations, querying, change tracking, security, and testing.

Monitor and react to content distribution lifecycle events using the Sling Distribution API, covering event handling, queue monitoring, and distribution tracking.

Analyze Azure resources and IaC files to identify cost optimization opportunities, calculate savings, and create GitHub issues for tracking.

Optimize Entity Framework Core queries by fixing N+1 problems, choosing correct tracking modes, using compiled queries, and avoiding common performance traps.

Add EAS Observe to an Expo project for startup, navigation, and custom-event performance tracking, query metrics via the EAS CLI, and interpret results.

Build video analytics pipelines using NVIDIA DeepStream SDK 9.0 with Python pyservicemaker API, including GStreamer-based video processing, TensorRT inference integration, object detection/tracking, and Kafka/message broker integration.

Performs STRIDE-A threat model analysis of repositories and systems, producing architecture overviews, DFD diagrams, prioritized findings, and executive assessments. Supports both single analysis and incremental updates with change tracking.