Databases
PostgreSQL Beginner to Intermediate
Foundations, CRUD, joins, views, CTEs, window functions, indexes, and query-plan basics for application engineers.
This repo is a compact shelf of standalone HTML handbooks for engineering, AI tooling, coding standards, and platform concepts. Each one is meant to be skimmed fast when you need the right pattern, command, or mental model.
Each card links directly to a handbook. The visual on top is an inline SVG, and the footer keeps the handbook name and entry link easy to reach.
Foundations, CRUD, joins, views, CTEs, window functions, indexes, and query-plan basics for application engineers.
Schemas, constraints, CRUD, joins, views, temp structures, flow control, and TRY/CATCH-oriented T-SQL fundamentals.
LATERAL, recursive CTEs, advanced grouping, procedures, PL/pgSQL functions, and JSONB patterns for deeper PostgreSQL work.
APPLY operators, ranking, recursive CTEs, PIVOT/UNPIVOT, stored procedures, iTVFs, and safe dynamic SQL in T-SQL.
Standards, testing, architecture, and modern Angular implementation patterns.
Reference notes for multi-agent design, orchestration, and production usage patterns.
Compute, cost, IaC, networking, and operational guidance for modern Azure delivery teams.
Compute, storage, networking, cost optimization, and security patterns for AWS with Terraform and Boto3.
Compute, BigQuery, networking, IAM hierarchy, cost management, and security patterns for Google Cloud.
Modes, models, hooks, agents, MCP integrations, and workflow guidance in one place.
Python-centric notes on pipelines, data modeling, orchestration, and foundational concepts.
DataFrames, Series, I/O, cleaning, transformation, groupby, merge, time series, and production patterns for pandas v2.x.
Clean coding conventions, project structure, patterns, and maintainability guidance for .NET teams.
Data prep, training strategy, evaluation, and operational considerations for tuning models.
QLoRA, SFTTrainer, PEFT, DPO, adapter workflows, and deployment patterns for modern open-weight LLM training.
Branching, pull request habits, merge safety, and team workflows for real repositories.
Chains, prompts, tools, retrieval, and application patterns across LangChain workflows.
State graphs, memory, agents, execution flow, and production orchestration with LangGraph.
Tracing, debugging, evaluation, and operational visibility for LLM applications and agents.
Core model ideas, prompting fundamentals, architecture terminology, and reference concepts.
Message design, few-shot patterns, reasoning strategies, RAG prompts, and structured JSON output guidance.
Machine learning basics, model types, metrics, workflows, and decision-making foundations.
Tensors, autograd, modules, data loading, training loops, and practical PyTorch patterns from beginner to intermediate.
DVC versioning, experiment tracking, FastAPI serving, Docker, monitoring, and production ML patterns.
Experiment tracking, sweeps, artifacts, dashboard workflows, and collaboration patterns for serious ML teams.
Developer-facing notes for Foundry concepts, workflows, and delivery patterns.
Embeddings, chunking, hybrid search, re-ranking, graph RAG, and evaluation patterns for high-signal context design.
API structure, coding standards, testing, and service design patterns in Python and FastAPI.
State management, component patterns, testing, and maintainable React plus Redux architecture.
Lightweight agent patterns, execution flow, and implementation guidance with SmolAgents.
Daily Docker commands, production Dockerfiles, container debugging, Podman tradeoffs, and orchestration guidance.
Experiment tracking, model registry, aliases, deployment, LLMOps, and production anti-patterns with MLflow 2.x.