Technical Section
Deep technical dives into Generative AI architectures, patterns, and skills
GenAI
LLMs, Agents, Vector DBs, ML Ops
Google Cloud
Compute, Vertex AI, GKE, Security
AWS
EC2, Bedrock, Sagemaker, Lambda
Azure
OpenAI Service, AKS, Cosmic DB
Claude Code
Anthropic, Agents, MCP, Hooks
Recursos
Roadmaps, repos e guias de carreira
Codex
OpenAI, CLI Agent, Code Generation
Category Name
LLM Fundamentals
The building blocks behind language models — from tokens and attention to RAG and prompt engineering.
Agents & Orchestration
Autonomous systems that plan, reason, and use tools. From single-agent loops to multi-agent pipelines.
Computer Vision
Models that see and interpret images, video, and visual data using modern deep learning architectures.
Voice AI & Audio
Speech recognition, synthesis, and real-time voice pipelines powering the next generation of voice interfaces.
Frameworks & Ecosystem
The SDKs, platforms, and cloud services that make building GenAI applications faster and production-ready.
LLM Observability Tools
Monitor, trace, and evaluate your LLM applications in production. Essential for reliability and cost control.
Data & Representations
How models store, retrieve, and reason over structured and unstructured data at scale.
Vector Databases
Purpose-built databases for similarity search over high-dimensional embeddings — the backbone of RAG.
Text Embeddings
Dense vector representations of text that power semantic search, clustering, and retrieval.
Data Extraction
Techniques and tools for parsing, structuring, and extracting information from unstructured documents.
Security, Governance & Compliance
Protecting GenAI systems against adversarial attacks, data leakage, and policy violations.
Evaluation & Quality
Metrics, benchmarks, and automated frameworks for measuring LLM quality and reliability.
Models & Strategies
The frontier models shaping the GenAI landscape — capabilities, trade-offs, and use cases.
Open LLMs Access
Open-weight models you can run locally or on your own infrastructure, without API dependency.
Infrastructure & Cloud
The compute, storage, and networking layer for training, serving, and scaling AI workloads.
Multimodal & Interfaces
Models that process and generate across text, image, audio, and video modalities.
Machine Learning
Classical and modern ML techniques that underpin deep learning and GenAI model development.
Performance & Cost
Techniques for reducing latency, improving throughput, and cutting inference costs without sacrificing quality.
LLMOps
CI/CD, experiment tracking, and deployment pipelines adapted for the lifecycle of LLM applications.
Integration & Automation
Connecting LLMs to APIs, databases, and workflows through function calling and event-driven patterns.
DevOps & Professional Deploy
Container orchestration, scaling strategies, and production-grade deployment for AI services.
GenAI Architecture
System design patterns for reliable, scalable, and maintainable Generative AI applications.
SaaS Tips
Learn to build a modern SaaS with Next.js, Artificial Intelligence, and quick MVPs using this highly popular stack.
Vercel
SaaS TipsAutomatic deployments, global CDN, Serverless Functions, and the best hosting for Next.js.
Supabase
SaaS TipsComplete PostgreSQL database, built-in auth, storage, and native pgvector support.
Resend
SaaS TipsSimplified transactional email delivery with high inbox placement and clean APIs.
AbacatePay
SaaS TipsIntegrated Brazilian payment processing: PIX, credit cards, and instant subscriptions.
PostHog
SaaS TipsProduct analytics, heatmaps, session recordings, and feature flags to understand user behavior.
GitHub Actions
SaaS TipsNative CI/CD: automatically lint, test, and deploy your app on every push or pull request.
Frontend Layer
$0 AI StackRoutes user requests with Next.js, Streamlit, and Vercel (free tier).
Agent Orchestrator
$0 AI StackThe system's brain that runs the end-to-end data flow with LangGraph and CrewAI.
RAG Pipeline
$0 AI StackRetrieval & indexing with Notion, Chroma storage, and a local Qdrant vector DB.
LLM Layer
$0 AI StackRun models locally with Ollama: Gemma 3 4B, Llama 3.3 70B, and Mistral Small 4.
Tool Use via MCP
$0 AI StackConnect agents to GitHub, Slack, databases, and files via the Model Context Protocol.
Code Agent
$0 AI StackWrite, debug, and generate code with Claude Code CLI and Aider.
Data Layer
$0 AI StackPersist application state with SQLite, DuckDB, and Supabase (free tier).
Deployment Layer
$0 AI StackShip for free with Docker, Cloudflare Workers, and Hugging Face Spaces.
Fundamentos e Gestão da Plataforma
Compute (Processamento)
Containers e DevOps
Storage (Armazenamento)
Bancos de Dados
Data & Analytics
Networking
Segurança e Identidade
Observabilidade e Operações
Inteligência Artificial e Machine Learning
Custos e FinOps
Fundamentos e Gestão da Plataforma
Compute (Processamento)
Containers e Orquestração
Storage (Armazenamento)
Bancos de Dados
Data & Analytics
Networking e Content Delivery
Segurança, Identidade e Compliance
Monitoramento e Operações
DevOps e Infraestrutura como Código
Inteligência Artificial e Machine Learning
Arquiteturas Serverless e Eventos
Custos e FinOps
Governança e Multi-Account
Fundamentos e Gestão da Plataforma
Compute (Processamento)
Containers e Orquestração
Storage (Armazenamento)
Bancos de Dados
Data & Analytics
Networking e Content Delivery
Segurança, Identidade e Compliance
Monitoramento e Operações
DevOps e Infraestrutura como Código
Inteligência Artificial e Machine Learning
Arquiteturas Serverless e Eventos
Custos e FinOps
Governança e Organização
Migração e Híbrido
Claude Code — Anthropic
Agentic CLI for software engineering — sub-agents, MCP, hooks, skills, plugins and agent teams.
Sub-agents
Claude CodeSpecialized agents that run in isolated context windows
Agent Teams
Claude CodeCoordinate multiple Claude Code instances in parallel
MCP
Claude CodeConnect Claude Code to external tools via Model Context Protocol
Discover Plugins
Claude CodeFind and install plugins from marketplaces to extend Claude Code
Skills
Claude CodeCreate custom slash commands and reusable Claude playbooks
Hooks Guide
Claude CodeRun shell commands automatically on Claude Code lifecycle events
Prompt Frameworks
Claude Code8 structured frameworks — CLARITY, SOCRATES, MAGIC and more — to get the best results from Claude
Token Limit Laws
Claude Code19 laws to stay under your Claude token limit — smart usage beats brute force
Connectors
Claude CodeConnect Claude to Google Workspace, GitHub, Slack, Jira and more — natively
Artifacts
Claude CodeLive interactive outputs — React apps, diagrams, SVGs and documents rendered inside your conversation
Codex — OpenAI
Agentic CLI platform for code, productivity & workflows — Computer Use, integrated browser, 90+ plugins.
Best Practices & Hooks
Workflow patterns, hooks, and orchestration guidelines for Codex CLI.
Key Features
What Codex does out of the box — agentic capabilities and platform integrations.
Computer Use
FeatureAutomates GUI tasks — clicks, forms, screenshots — across desktop apps.
Integrated Browser
FeatureBuilt-in browser for web dev, scraping and live preview during coding.
Terminal Execution
FeatureRuns shell commands, tests, builds and Git operations autonomously.
File Read/Edit
FeatureReads, edits and refactors files across your entire repo with context.
90+ Plugins
FeatureExtensible marketplace — Slack, Jira, Notion, GitHub and more.
PR Automation
FeatureOpens, reviews and iterates on pull requests end-to-end.
Core Concepts
From codex-cli-best-practice — the building blocks of agentic engineering with Codex CLI.
Commands
ConceptBuilt-in slash commands: /plan, /fast, /fork, /review, /status, /mcp, /agent, /apps, /model, /permissions.
Subagents
Concept.codex/agents/<name>.toml — custom agents with TOML role configs, parallel orchestration, CSV batch processing. Built-in: default, worker, explorer.
Skills
Concept.agents/skills/<name>/SKILL.md — reusable instruction packages with progressive disclosure (scripts/, references/, assets/). Invoke via /skills or $skill-name.
Plugins
Concept.codex-plugin/plugin.json — distributable bundles combining skills + app integrations + MCP servers. Built-in: $plugin-creator.
Marketplace
Conceptv0.121.0+ plugin catalog system. codex plugin marketplace add|upgrade|remove accepts GitHub shorthand, git URLs, local dirs.
Memories
Conceptv0.119.0+ cross-session memory pipeline. Enable via [features] memories = true. TUI control via /memories. Per-user scope.
MCP Servers
ConceptModel Context Protocol — STDIO + Streamable HTTP. OAuth, MCP Apps (resource reads, elicitations), parallel calls (v0.121.0+).
Config (config.toml)
ConceptTOML layered config — profiles, sandbox, approval policy, [features], [otel], [tui], model providers, granular approvals.
Rules
Concept.codex/rules/ — Starlark command execution policies via prefix_rule(): allow, prompt, forbidden. Test via codex execpolicy check.
AGENTS.md
ConceptProject context — hierarchical discovery from cwd to repo root, capped at 32 KiB. AGENTS.override.md for personal overrides.
Hooks (beta)
Concept.codex/hooks.json — user-defined shell scripts injected into the agentic loop for logging, security scanning, validation. Requires codex_hooks = true.
Speed (Fast Mode)
ConceptFast Mode (1.5x speed, 2x credits) on gpt-5.4 — toggle with /fast on|off|status. GPT-5.3-Codex-Spark for near-instant iteration (Pro).
Code Review
Concept/review — review branches, uncommitted changes, or specific commits. Configurable review_model in config.toml.
AI Terms
ConceptAgentic Engineering · Context Engineering · Vibe Coding — the language of modern AI-assisted development.
Orchestration Workflow
ConceptEnd-to-end pattern: Agent → Skill → Output. e.g. fetch weather (Open-Meteo) and invoke SVG creator skill.
Development Workflows
All major workflows converge on: Research → Plan → Execute → Review → Ship.
Superpowers
⭐ 171kbrainstorming → writing-plans → subagent-driven-development → TDD → code-review → finish-branch.
Spec Kit
⭐ 92k/speckit.constitution → /speckit.specify → /speckit.plan → /speckit.tasks → /speckit.implement.
gstack
⭐ 86k/office-hours → plan-reviews (CEO/Eng/Design) → implement → /review → /qa → /ship → /land-and-deploy.
Get Shit Done (GSD)
⭐ 58k/gsd-new-project → discuss → plan → execute → verify → ship → complete-milestone.
oh-my-codex
⭐ 27k$deep-interview → $ralplan → $ralph — opinionated Codex skill stack.
Compound Engineering
⭐ 16k/ce-ideate → brainstorm → plan → work → code-review → compound → repeat.
Tips & Tricks (50)
Battle-tested patterns from the Codex community — Prompting, Planning, Agents, Skills, Hooks, Workflows, Git/PR, Debugging.
Prompting (3)
Tips- Challenge Codex — "prove this works" and diff main vs branch.
- After a mediocre fix: "scrap this, implement the elegant solution".
- Paste the bug, say "fix" — don't micromanage.
Planning (4)
Tips- Use /plan for explicit plans on multi-step tasks.
- Phase-wise gated plans with unit + integration + automation tests.
- Spin up a 2nd Codex (cross-model) to review your plan.
- Detailed specs reduce ambiguity — more specific = better output.
AGENTS.md (5)
Tips- Keep concise — ~150 lines (32 KiB byte cap).
- Use AGENTS.override.md for personal prefs.
- Any dev should run "run the tests" and have it work first try.
- Finish migrations — partial state confuses models.
- Use config.toml for harness-enforced behavior, not AGENTS.md.
Agents (3)
Tips- Feature-specific sub-agents with skills > generic qa/backend.
- Multi-agent throws compute at problems, keeps main context clean.
- Test-time compute: separate windows make results better.
Skills (7)
Tips- Clear name + description frontmatter for auto-discovery.
- Skills are folders — references/, scripts/, examples/.
- Build a Gotchas section in every skill.
- Description is a trigger, not a summary.
- Don't state the obvious — push out of default behavior.
- Don't railroad — give goals and constraints, not steps.
- Use the built-in skill creator to scaffold.
Hooks (3)
Tips- Logging, security scanning, validation (codex_hooks = true).
- Auto-format code so Codex output passes CI.
- Branch SessionStart on startup|resume|clear (v0.120.0+).
Memories (2)
Tips- Enable once — consolidation runs between sessions.
- Set no_memories_if_mcp_or_web_search = true for sensitive threads.
Workflows (4)
Tips- Vanilla Codex beats workflows on small tasks.
- Use profiles for project-defined safety levels.
- Start with on-request approval — escalate to never when confident.
- Use /fork to explore alternatives, /resume to pick up.
Workflows Advanced (5)
Tips- Multi-agent for parallel fan-out (GA, default on).
- codex exec for headless/CI pipelines.
- workspace-write + on-request is a great default combo.
- Git worktrees for parallel development.
- ASCII diagrams to understand your architecture.
Git / PR (3)
Tips- Small focused PRs — one feature, easy revert.
- Squash-merge: clean linear history, easy bisect.
- Commit often — as soon as a task is completed.
Debugging (5)
Tips- Run the noisy terminal as a background task.
- MCP (Chrome DevTools, Playwright) for browser console logs.
- Take screenshots and share when stuck.
- Different model for QA (e.g. Claude Code for review).
- Agentic search (glob + grep) beats RAG.
Utilities (4)
Tips- iTerm / Ghostty / tmux > IDE (VS Code/Cursor).
- Wispr Flow for voice prompting (10x).
- codex-cli-hooks for feedback loops.
- Explore config.toml profiles, sandbox modes, MCP.
Daily (2)
Tips- Update Codex CLI daily.
- Start your day reading the changelog.
Articles & Tweets
Deep dives, AMAs and announcements from the Codex team and community.
How Codex is built
Tibo90% self-built in Rust — Tibo on Pragmatic Engineer (17 Feb 2026).
Skills in Codex
EmbiricosStandardizing .agents/skills across agents — Embiricos (Feb 2026).
Unrolling the Codex agent loop
TweetHow Codex works internally — Bolin (Jan 2026).
AMA with Codex team
RedditCLI, sandbox, agents — Embiricos, Fouad, Tibo + team (May 2025).
Codex CLI first look
TweetOpen-source local coding agent — Fouad + Romain (Apr 2025).
Videos & Podcasts
Listen to the people building Codex talk about how they build, ship, and dogfood it.
Power user's guide to Codex
EmbiricosParallelizing workflows, planning, context engineering — Embiricos (How I AI, 2026).
Scaffolding is coping not scaling
TiboLessons from Codex — Tibo (Dev Interrupted, 2026).
How Codex team uses their agent
TiboTibo + Andrew (Every, 18 Feb 2026).
Dogfood — building Codex with Codex
TiboTibo (Stack Overflow, 24 Feb 2026).
Why humans are AI's biggest bottleneck
EmbiricosCodex product vision — Embiricos (Lenny's Podcast, Feb 2026).
OpenAI and Codex
TiboTibo + Ed Bayes (Software Engineering Daily, 29 Jan 2026).
Learning Resources
Cookbooks, guides and reference material to master Codex.
Top 20 Most Starred Repositories (20)
The most famous and well-rated repositories from the AI and development open source community.
donnemartin/system-design-primer
⭐ 346.9k stars — System Design Primer
TheAlgorithms/Python
⭐ 220.7k stars — Algorithms in Python
ultraworkers/claw-code
⭐ 189.8k stars — Claude Code extensions
affaan-m/everything-claude-code
⭐ 172.5k stars — Claude Code Resources
huggingface/transformers
⭐ 160.2k stars — Transformers Library
anomalyco/opencode
⭐ 153.9k stars — Open Source Code
anthropics/skills
⭐ 127.6k stars — Anthropic Skills
shadcn-ui/ui
⭐ 113.5k stars — React Components
forrestchang/andrej-karpathy-skills
⭐ 108.0k stars — Karpathy Skills
github/spec-kit
⭐ 92.3k stars — GitHub Spec Kit
microsoft/ML-For-Beginners
⭐ 85.6k stars — ML for Beginners
karpathy/autoresearch
⭐ 78.6k stars — Auto Research
dair-ai/Prompt-Engineering-Guide
⭐ 74.1k stars — Prompt Engineering
openai/openai-cookbook
⭐ 73.2k stars — OpenAI Cookbook
labmlai/annotated_deep_learning_paper_implementations
⭐ 66.5k stars — Deep Learning Papers
paperclipai/paperclip
⭐ 61.9k stars — Paperclip AI
microsoft/ai-agents-for-beginners
⭐ 60.4k stars — Agents for Beginners
gsd-build/get-shit-done
⭐ 59.6k stars — Get Shit Done
DS4SD/docling
⭐ 59.1k stars — Docling PDF Parser
MemPalace/mempalace
⭐ 50.9k stars — Memory Architecture
Claude Code & Coding Agents (17)
Plugins, skills, sub-agents e ferramentas para Claude Code, Codex e harnesses de IA.
claw-code
CLI agent em Rust construído sobre oh-my-codex.
everything-claude-code
Performance optimization system — skills, instincts, memory, security.
opencode
The open source coding agent.
anthropics/skills
Repositório oficial de Agent Skills da Anthropic.
andrej-karpathy-skills
CLAUDE.md derivado das observações de Karpathy sobre LLM coding pitfalls.
get-shit-done
Meta-prompting, context engineering e SDD para Claude Code (TÂCHES).
claude-code-best-practice
Práticas de Claude Code.
antigravity-awesome-skills
1.273+ skills agentic instaláveis (Claude Code, Cursor, Codex, Gemini CLI).
NemoClaw
Plugin NVIDIA para instalação segura do OpenClaw.
awesome-claude-code-subagents
100+ sub-agents especializados para Claude Code.
llm-council
Conselho de LLMs trabalhando juntos para responder perguntas difíceis (Karpathy).
codex-plugin-cc
Use Codex de dentro do Claude Code para review/delegar tarefas.
mcp_excalidraw
MCP server + skill para Excalidraw — toolkit de diagramas via agentes.
hve-core
Hypervelocity Engineering — instructions, prompts, agents e skills.
agentlytics
Dashboard de analytics para agentes de código (Cursor, Windsurf, Claude Code, Copilot).
claude-council
Plugin Claude Code para consultar múltiplos agentes (Gemini, OpenAI, Grok).
claude-code-hooks
Hooks & extensions for Claude Code workflow automation.
AI Agents & Frameworks (13)
Protocolos, frameworks e cursos para construir agentes de IA.
autoresearch
Agentes de IA rodando research em treino single-GPU nanochat.
paperclip
Orquestração open-source para zero-human companies.
ai-agents-for-beginners
12 lições para começar a construir agentes (Microsoft).
agents-course
Curso oficial Hugging Face Agents.
agentscope
Agentes que você pode ver, entender e confiar.
A2A
Protocolo aberto para comunicação entre agentes.
GenAI_Agents
Tutoriais e implementações de técnicas Generative AI Agents.
feynman
Companion AI.
OpenSpace
Make Your Agents: Smarter, Low-Cost, Self-Evolving.
beeai-framework
Framework IBM para agentes production-ready — orquestração, memória, tools, observability.
a2a-python
SDK oficial Python do Agent2Agent (A2A) Protocol.
awesome-ai-agents-2026
300+ recursos · 20+ categorias de agentes em 2026.
IBM/mcp
Coleção IBM de servidores Model Context Protocol — integrações enterprise prontas.
RAG & Knowledge (7)
Frameworks de RAG, knowledge graphs e memória para agentes.
docling
Converte PDFs, DOCX, PPTX e imagens em markdown estruturado para ingestão LLM (IBM).
mempalace
Sistema de memória de IA com maior pontuação já benchmarked. Free.
llama_index
Framework líder para pipelines RAG — document loaders, vector stores, query engines.
RAG_Techniques
Técnicas avançadas de Retrieval-Augmented Generation.
haystack
Framework end-to-end NLP para RAG, QA e document search. Production-ready, 40+ backends.
RAG-Anything
All-in-One RAG Framework (HKUDS).
Understand-Anything
Knowledge graphs interativos a partir de qualquer código/base.
LLMs & Local Inference (7)
Modelos abertos, fine-tuning e interfaces locais.
transformers
Biblioteca definitiva HuggingFace — BERT, GPT, T5, LLaMA. Comece aqui para qualquer task NLP.
openai-cookbook
Exemplos oficiais OpenAI API — embeddings, function calling, assistants, batch processing.
text-generation-webui
Interface local para LLMs — text, vision, tool-calling, training.
diffusers
Modelos de difusão state-of-the-art para imagem, áudio e vídeo — Stable Diffusion, DALL·E.
WeClone
Crie seu AI twin a partir de chat history — fine-tune LLMs.
Kimi-K2.5
Modelo mais potente da Moonshot.
granite-cookbook
Receitas práticas para IBM Granite — fine-tuning, RAG, tool use e enterprise deployment.
Spec-Driven Development (5)
Specs executáveis, reverse engineering e arquiteturas teóricas.
spec-kit
Toolkit GitHub para Spec-Driven Development.
OpenSpec
Spec-driven development para AI coding assistants.
rtk
CLI proxy que reduz consumo de tokens em 60-90% (Rust).
OpenMythos
Reconstrução teórica da arquitetura Claude Mythos.
reversa
Transforma sistemas legados em specs executáveis para agentes.
Observability & Infra (5)
Plataformas open-source para observability, gateways e DevOps.
harness
Plataforma end-to-end de developer — SCM, CI/CD, dev environments.
langfuse
LLM engineering platform — observability, evals, prompt management.
openobserve
Plataforma open-source de observability — logs, metrics, traces.
genai-toolbox
MCP Toolbox para databases (Google).
OmniRoute
AI gateway multi-provider com smart routing, retries e fallbacks.
UI / Frontend (2)
Componentes acessíveis e animações para interfaces modernas.
Career & Productivity (3)
AI para trabalho, planejamento pessoal e automação.
Security & CLI (7)
Ferramentas de pentest e CLIs agent-native.
CLI-Anything
Tornar todo software agent-native via CLI.
strix
AI hackers open-source para encontrar e corrigir vulnerabilidades.
TracerAi
Brain de IA para plataforma TracerAI — Python/FastAPI + GeoIP + scikit-learn.
codex-cli-hooks
Hooks & extensions for Codex CLI workflow integration.
codex-cli-best-practice
Best practices & guidelines for Codex CLI usage.
gemini-cli-hooks
Hooks & automation for Gemini CLI integration.
gemini-cli-best-practice
Best practices for Gemini CLI development.
Roadmaps & Awesome Lists (7)
Listas curadas, roadmaps e guias de carreira em IA/Data Science.
Prompt-Engineering-Guide
Guides, papers, lessons sobre prompt engineering, RAG e agents.
ai-engineering-hub
Coleção curada de projetos reais — RAG systems, agents, fine-tuning pipelines.
awesome-datascience
Repositório awesome de Data Science para problemas reais.
awesome-project-ideas
Curated list de ideias ML, NLP, Vision, Recommender Systems.
data-scientist-roadmap
Tutorial e grafo do Data Science Roadmap.
DataScienceResources
Open Source Data Science Resources.
Data-science-best-resources
Links curados de recursos para data science.
ML & Data Science Foundations (29)
Cursos, livros e exemplos clássicos de Machine Learning, NLP e estatística.
system-design-primer
⭐ 346.9k stars — Learn how to design large-scale systems. Prep for the system design interview (donnemartin).
All-algorithms-implemented-in-Python
Todos algoritmos implementados em Python (TheAlgorithms).
ML-For-Beginners
12 semanas, 26 lições, 52 quizzes de ML clássico (Microsoft).
annotated_deep_learning_paper_implementations
Implementações anotadas de papers DL — transformers, GANs, RL, optimizers.
Made-With-ML
Curriculum MLOps end-to-end — design, train, serve, monitor com CI/CD.
ai-for-beginners
Currículo de 12 semanas — neural nets, NLP, computer vision (Microsoft).
fastbook
Livro/curso fast.ai sobre Deep Learning for Coders.
nn-zero-to-hero
Curso de Karpathy construindo redes neurais do zero — micrograd, makemore, GPT.
folium
Python data + Leaflet.js maps.
devops-master-class
Tutorial DevOps — Docker, Kubernetes, Terraform, Ansible, Jenkins.
shiny-examples
Exemplos oficiais Shiny (RStudio).
code
Códigos R e Python (Data Professor).
youtube_tutorials
Scripts dos tutoriais LucidProgramming no YouTube.
The_Math_of_Intelligence
Syllabus do curso "The Math of Intelligence" (Siraj).
A_Guide_to_Running_Tensorflow_Models_on_Android
Code do guia TensorFlow no Android (Siraj Raval).
data
Datasets para prática de ML (Data Professor).
CanalSandeco
Arquivos dos vídeos do Canal Sandeco.
Classifying_Data_Using_a_Support_Vector_Machine
SVM gradient descent (Siraj Raval).
aprendendo-django
Aprendendo Django — Marinho Brandão.
Google_Dopamine_LIVE
Code do "Google Dopamine (LIVE)" by Siraj Raval.
BigDataAnalyticswithSpark
Big data analytics com Apache Spark (Scala).
DSE210x-Statistics-and-Probability
UCSanDiegoX edX DSE210x — Stats e Probability em Python.
CoronaMaskOn
Mask On-Off control com computer vision.
states-cities-brazil
🇧🇷 Base de estados e cidades do Brasil.
Scala-and-Spark-for-Big-Data-Analytics
Scala and Spark for Big Data Analytics (Packt).
DemoNeuralNet
Toy project — neural net simples em R.
PythonFundamentos
Repositório do Curso Online Python Fundamentos.
llm-bootcamp
Full Stack Deep Learning — protótipo a produção, infra, deploy, monitoring.
spendkey-backend-assessment
SpendKey Backend Technical Assessment.