AI and machine learning,
explained so you can actually build things.
Deep-dive articles, tutorials and topic guides spanning classic ML, generative AI, LLMs, RAG, agents and cloud AI — written for engineers, data professionals, architects and product teams who want to ship, not just read.
Fresh from the blog
Liver Fibrosis Risk Assessment
Beyond Fatty Liver Detection: A GenAI Framework for Liver Fibrosis Risk Assessment Using FibroScan and Blood Reports
Building a Diet AI Assistance App having Converstational feature build using Amazon Bedrock, RAG Knowledge Bases, Cognito, API Gateway, Lambda, DynamoDB
Learn how to design a secure, serverless, multi-user AI Diet Assistant using Amazon Bedrock, RAG, Knowledge Bases, Amazon Cognito, API Gateway, Lambda, DynamoDB
Malicious URL Detection Using AI/ML: A Multi-Class Classification Approach
Learn how to build a scalable multi-class machine learning pipeline using 110 engineered lexical, domain, and short-URL features to detect web threats with 95% accuracy.
Learn by topic
Linear & Logistic Regression
24 postsFoundational predictive models — the workhorses of applied ML.
Trees & Ensembles
18 postsDecision trees, random forests, XGBoost, LightGBM.
Deep Learning
42 postsNeural networks from perceptrons to transformers.
Natural Language Processing
31 postsTokenization, embeddings, LLMs and beyond.
Computer Vision
26 postsCNNs, object detection, segmentation, diffusion.
Time Series Forecasting
15 postsARIMA, Prophet, and neural forecasters for temporal data.
One practical AI idea, every Wednesday.
Short, honest and practical — from classic ML to LLMs and agents. No hype threads.