Contents? Let me provide a real, personal example.In this article, I’ll cover:When to fine-tuneWhen to use RAGThe mathematical intuition behind LoRA/QLoRALoRA (Low Rank Adaptation)The core intuition of LoRAWhat this means for practicionersQLoRA (Quantized Low Rank Adaptation)4-bit NormalFloat (NF4)Double QuantizationPaged OptimizersWhy QLoRA instead of full fine-tuning?The technical implementation detailsGenerating high quality training dataWhy 4 different inputs …

How to Fine-Tune an LLM: An End-to-End Guide Read More »

  Building an agent that works in a notebook takes an afternoon. Getting that same agent to survive real traffic, recover from a crash at 3 am, and not leak someone else’s data while it runs large language model (LLM)-generated code is a different job entirely, and it’s the job most teams underestimate. Only a …

5 Tools for Building and Deploying AI Agents in Production Read More »

ContentsTL;DRThe Assumption I Went In WithWho This Is ForBuilding the ExperimentComponent 1: The Topology GeneratorComponent 2: The Agent PolicyComponent 3: The DiagnosticsWhat I DidWhat I GotLooking Underneath the Number That Didn’t MovePerformance CharacteristicsHonest Design Decisions1. The Deterministic Agent Policy2. Standard Library Keyword Matching3. Removing Circular Early Exits4. Budget Size and Ceiling Effects5. Dependency FootprintTrade-Offs and …

Graph Engineering Isn’t About More Connections — It’s About Which Ones Get Used Read More »

Contents# Introduction# 1. pyjanitor for Fluent, Chainable DataFrame Cleaning# 2. Great Expectations for Data Validation and Quality Checks# 3. ftfy for Fixing Broken Unicode and Text Encoding Problems# 4. ydata-profiling for Instant Dataset Audits# 5. Cerberus for Lightweight Schema Validation on Arbitrary Data Structures# Summary and Next Steps # Introduction  Data cleaning is rarely interesting, but it does consume the majority of a …

5 Python Libraries That Make Data Cleaning More Enjoyable Read More »

, the good folks at DuckDB released a database communication protocol called Quack. Its main aim was to allow DuckDB databases held on different servers to communicate with each other over HTTP in a client/server arrangement and allow them to read and write each others data. In other words, using the Quack protocol, DuckDB sitting …

Running SQL Concurrently Across Three Remote DuckDB Servers with Quack Read More »