Results for “minervini”

Uruchamianie i wdrażanie platformy Soneta (enova365, Triva) w kontenerach. Używaj gdy użytkownik: (1) stawia środowisko (server + web) na obrazach Soneta przez `docker compose` albo na Apple `container` / Container Desktop; (2) tworzy bazę danych w kontenerze (usługa init z `dbmgr create`, `--demo`, `--recreate`, licencja, konwersja); (3) wdraża na Kubernetes przez Helm (`helm repo add soneta`, `values.yaml`, `dblist`, `adminMode`); (4) wybiera wersję obrazów (tagi z Docker Hub `soneta/*` lub `registry.soneta.pl`), architekturę (alpine/arm64/amd64), logowanie do registry; (5) potrzebuje SQL Servera — zewnętrznego (`host.docker.internal` / `host.containers.internal`) albo jako kontener `mssql`; (6) rozwiązuje problemy startu stacku (kolejność, port zajęty, brak DNS między usługami w Apple container, zły host-alias). Słowa kluczowe: docker compose, docker-compose.yaml, apple container, Container Desktop, helm, kubernetes, obraz, tag, wersja, mssql, dbmgr, x-init, server.standard, web.standard.

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.

Managed vector database for production AI applications. Fully managed, auto-scaling, with hybrid search (dense + sparse), metadata filtering, and namespaces. Low latency (<100ms p95). Use for production RAG, recommendation systems, or semantic search at scale. Best for serverless, managed infrastructure.

Use when filtering `RNAsubopt -s` output to keep p-optimal RNA structures in a ViennaRNA post-processing pipeline.

Data Version Control for ML projects. Track large datasets and models alongside Git, build reproducible ML pipelines, and run experiments with metric comparison. Works with any storage backend including S3, GCS, Azure, and local filesystems.

Exploit validation and exploitation using Metasploit Framework. Runs in a dedicated Docker container (separate from Kali). Validates CVEs discovered by nuclei, nikto, or other scanners with actual exploit modules. Covers exploit selection, payload configuration, exploitation, and post-exploitation pivoting. Uses msfconsole, msfvenom, and the Metasploit module database. Chains from /pentester, /analyze-cve, or /post-exploit when exploitable CVEs are confirmed.

Infer gene regulatory networks (GRNs) from expression matrices using arboreto's scalable GRNBoost2 and GENIE3 tree-ensemble algorithms with Dask-distributed computation. Use when analyzing bulk or single-cell RNA-seq transcriptomics to map transcription-factor-to-target-gene regulatory interactions, build adjacency networks, or run the GRN-inference step of a SCENIC pipeline on large datasets. Part of the AlterLab Academic Skills suite.

Provides code examples and best practices for using Pinecone, a managed vector database for production RAG, recommendation, and semantic search applications.

Mine LITCOIN — a proof-of-comprehension and proof-of-research cryptocurrency on Base. Use when the user wants to mine crypto with AI, earn tokens through reading comprehension or solving optimization problems, stake LITCOIN, open vaults, mint LITCREDIT, manage mining guilds, deploy autonomous agents, or interact with the LITCOIN DeFi protocol.