AI Engineering
Practical AI projects, experiments, tutorials, and applied research.
Transfer Learning for Vision
Ever wondered how AI can detect cancer from scans or spot heart disease in an X-ray — without being trained on millions of medical images?
Here’s the secret: Transfer Learning.
Instead of building models from scratch, researchers take…
Transfer Learning for NLP
Ever wondered how AI learns new languages so quickly — or how ChatGPT seems to instantly “get” what you’re saying?
That’s the power of transfer learning in Natural Language Processing (NLP) — where AI learns language the…
Transfer Learning – Beginners Guide
From cats on the internet to cancer detection in hospitals — how does one AI model jump across worlds?
That’s the magic of transfer learning. In this first post of my new AI series, I break it…
Detecting Plant Diseases with AI – A Beginner-Friendly Deep Learning Project
🌱 Can AI Really Spot Plant Diseases?
Yes! In my latest beginner-friendly blog, I share how I built an AI model that detects plant leaf diseases using deep learning. From a free dataset to training a modern…
How I built a beginner-friendly skin-cancer detector
Ever wondered how AI can spot skin cancer from images? My easy guide walks you through HAM10000 with a Colab + GitHub project. Click to explore!
Visualising Change from Space — A Beginner’s Guide to ML with Satellite Data – Part 1
Explore how machine learning and satellite imagery can reveal how cities grow, how nightlights change, and how vegetation evolves. Three notebooks (India nightlights, Delhi urban map, Singapore NDVI) walk beginners step-by-step from visualization to a supervised…
AI Engineering brings together practical AI projects, experiments, tutorials, and applied research notes on building real-world AI systems. The goal is to make AI engineering easier to understand through concrete examples, beginner-friendly explanations, and practical implementation notes.