Blog
Insights and technical guides on AI, machine learning, and data engineering.
Insightful AI Service: How to Analyse YouTube Channels and Generate Content Ideas
A practical guide to building an insightful AI pipeline that scrapes YouTube data, analyses sentiment with GPT, identifies content gaps, and generates high-potential video ideas using LLMs and EDA.
RAG Chatbot Service: How to Build a Conversational AI for Business Documents
A practical guide to Retrieval-Augmented Generation (RAG) — how to convert PDFs, websites, and documents into an interactive chatbot for document Q&A, product search, and business knowledge assistants.
How to Find the Nearest Location Using Python Geospatial Analysis
Step-by-step guide to building a geospatial route optimisation system in Python — detecting suburb polygons, calculating shortest paths with Dijkstra's algorithm, and finding the nearest location from any address in Brisbane.
Build an AI Content Generation Pipeline with GPT and Google Trends
How to build an automated content pipeline using GPT and Google Trends API — generate SEO-optimised articles, rank them against trending keywords, and auto-publish to your website using Python.
History of Automation: From the Jacquard Loom to AI Chatbots
A complete history of automation — tracing the journey from the Jacquard loom and steam engine through the Internet, deep learning, and ChatGPT, and what it means for the future of AI.
How Attention Mechanisms Work in Large Language Models (LLMs)
A clear explanation of attention mechanisms in Large Language Models — why they are critical, how they work with query-key-value operations, and a practical comparison showing LLM responses with and without attention.
How YOLO Object Detection Works: A Deep Neural Network Analysis
A visual deep-dive into how YOLO processes images layer by layer — exploring convolutions, batch normalization, and how deep CNNs transform pixel data into real-time object detections.
Genetic Algorithms Explained: From Basics to Python Implementation
A comprehensive beginner's guide to Genetic Algorithms — covering genes, chromosomes, mutation, crossover, and fitness functions, with a hands-on Python implementation solving the N-Queen problem.
How to Structure DBT Models for Complex Data Pipelines
A practical guide to applying modular programming in SQL using DBT — covering staging, intermediate, and final model layers with a real-world shopping example for data engineers.
GPT-5 vs GPT-4.5 for Code Generation and Debugging: A Real Test
A hands-on experiment comparing GPT-5 and GPT-4.5 Turbo on SQL debugging tasks — revealing why GPT-5 may have hit the S-curve ceiling and what it means for AI-assisted development.
AI as a Service Components: Data, Model, and Insight Explained
A breakdown of the three core components of AI as a Service (AIaaS) — Data, Model, and Insight — and how they work together to bring AI use cases to market for businesses.
What Is AI as a Service (AIaaS)? A Business Guide
A practical guide to AI as a Service (AIaaS) — what it is, why businesses are adopting it, and how it powers real-world AI solutions without building from scratch.