Machine learning

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…

Neon Realtime makes any SQL query live.

Use when the user asks about finding the best, top, or recommended model for a task, wants to know what AI model to use, or wants to compare models by…

One API and one credential for frontier and open-source LLMs and embedding models, built into your Neon branch and powered by Databricks.

Add Weave tracing to Python or TypeScript agents and LLM applications.

Create and manage Elastic ML anomaly detection jobs via the API.

Explain Elasticsearch ML anomaly detection scores, model behavior, and result interpretation.

Elastic ML anomaly detection — investigation/RCA, score explanation, job lifecycle troubleshooting, and job operations.

Build and publish a Gradio demo on Hugging Face Spaces for a user-provided LoRA.

Track and visualize ML training experiments with Trackio.

AI demos and GPU compute with Gradio Spaces and Hugging Face Spaces ZeroGPU.

Answer questions about LLM and agentic-application behavior from data already ingested into Elastic: latency and error rate, token and cost utilization…

Triage a degraded or suspect service end to end: read SLO status and burn rate, check active alerting rules and ML anomalies, measure throughput, latency, and…

Use Netlify AI Gateway to call OpenAI, Anthropic Claude, Google Gemini, TypeSafe (Jev), or OpenRouter-hosted models (xAI/DeepSeek/Meta/Mistral/Qwen) from…

Use this skill for Hugging Face Dataset Viewer API workflows that fetch subset/split metadata, paginate rows, search text, apply filters, download parquet…

Hugging Face CLI to estimate the required memory to load Safetensors or GGUF model weights for inference from the Hugging Face Hub

Train or fine-tune language and vision models using TRL (Transformer Reinforcement Learning) or Unsloth with Hugging Face Jobs infrastructure.

Redis Search guidance covering FT.CREATE schema design, field type selection (TEXT, TAG, NUMERIC, GEO, GEOSHAPE, VECTOR, JSON path), DIALECT 2 query syntax…

Redis LangCache guidance for semantic caching of LLM responses on Redis Cloud — calling search/set via the SDK or REST API, tuning the similarity threshold…

Migrate an application with hardcoded LLM prompts to a full LaunchDarkly AgentControl implementation in five stages: audit the code, wrap the call, move the…

Reference architecture for building a Generative AI (生成AI) workload for financial institutions on AWS, based on the closed-network edition of the AWS Samples…

Attach judges to config variations for automatic LLM-as-a-judge evaluation.

Secures and rate limits backend services behind Google Cloud API Gateway across OpenAPI 2.0 and OpenAPI 3.0.x API configurations, including MCP-enabled…