Machine learning

Use for GPU-accelerated machine learning on tabular data using NVIDIA cuML.

Hugging Face Hub CLI (`hf`) for downloading, uploading, and managing models, datasets, spaces, buckets, repos, papers, jobs, and more on the Hugging Face Hub.

Post-train LLMs with TRL (Transformers Reinforcement Learning) — SFT, DPO, GRPO, KTO, and reward-model training.

A.I.G Scanner — AI security scanning for infrastructure, AI tools / skills, AI Agents, and LLM jailbreak evaluation via Tencent Zhuque Lab AI-Infra-Guard.

Detect indirect prompt injection (goal hijack).

Detect persistent-memory poisoning and RAG/knowledge-base contamination via dialogue testing.

Create a SageMaker endpoint (real-time, real-time scale-to-zero, or async) with autoscaling, CloudWatch alarms, and tagging enabled by default.

Pick the right serving container for a SageMaker model deployment and find its current image URI.

Build, deploy, and maintain applications on Hugging Face Spaces — Gradio / Docker / Static SDKs, ZeroGPU and dedicated hardware, model loading, debugging…

Train or fine-tune sentence-transformers models across `SentenceTransformer` (bi-encoder, dense or static embedding model for retrieval, similarity…

Use ElevenLabs Realtime models (`eleven_realtime_v1_mini`, `eleven_realtime_v1_max`), the low-latency models built for voice conversation.

Plan and coordinate the deployment of a model to Amazon SageMaker AI.

Use when the user wants to provision infrastructure or third-party services using Stripe Projects.

Getting a first Qdrant Managed Cloud cluster running and connected safely: Free, Standard, and Premium tiers, choices that can't be changed later, creating…

Guides embedding model migration in Qdrant without downtime.

Guides tenant isolation architecture in Qdrant for multi-tenant or multi-user applications.

Covers everything about search in MongoDB: Atlas Search (full-text), Vector Search (semantic), and Hybrid Search.

Diagnoses and improves Qdrant search relevance.

Use this skill when diagnosing IAM and access failures for Bedrock and SageMaker.

Use this skill for GPU training or inference clusters on SageMaker HyperPod (Slurm or EKS), ParallelCluster, or self-managed EC2/EKS GPU instances.

Cost guardrail for AWS DevOps Agent that covers ALL AWS services and native agent tools.

Amazon SageMaker AI Operational Review.

Overview of Neon, a complete set of cloud backend primitives around Lakebase Postgres: Auth, Object Storage, Functions, the AI Gateway, and Realtime.

Guides and best practices for working with Lakebase Postgres on Neon: connections, pooled vs direct, schema migrations, branching, autoscaling, scale-to-zero…