Articles & Tutorials
149 technical articles covering AI, Machine Learning, Cybersecurity, Data Science, and Programming. Practical guides, tutorials, and deep dives — written for developers.
68 articles · Hashing
JWT Explained: Header, Payload and Signature
Key Takeaway --> A JWT is three Base64URL-encoded parts separated by dots: header (algorithm), payload (claims), and signature (integrity)…
How HTTPS and TLS Actually Work
Key Takeaway --> HTTPS is HTTP running over TLS. The TLS handshake performs three critical functions in a single exchange: negotiating enc…
Hashing vs Encryption vs Encoding: What's the Difference?
Key Takeaway --> Hashing verifies integrity and stores passwords safely. Encryption keeps data confidential with a key. Encoding converts …
Data Versioning Explained: Why Git Alone Isn't Enough for Data Science
Key Takeaway --> Git is excellent for tracking code, but it was never designed for large datasets, models, or ML pipelines. Data versionin…
Feature Engineering in the Age of AI
Key Takeaway --> Classical feature engineering uses domain expertise to create interpretable features. Embeddings capture semantic meaning…
GGUF Explained: The Practical Guide to Local LLM Model Files
GGUF (GPT-Generated Unified Format) is the standard file format for running LLMs locally. It packages model weights, metadata, and tokenize…
LLM Quantization Explained: 4-bit vs 8-bit Models
Quantization reduces model precision to save memory and increase speed. A 7B parameter model shrinks from 28 GB (FP32) to 3.5 GB (INT4) whi…
Running LLMs on CPU: What Actually Matters?
CPU inference speed depends primarily on memory bandwidth and model size—not CPU cores. A well-quantized 7B model on a modern CPU can gener…
Why Choose a Local Runtime?
Ollama, llama.cpp and LM Studio are the three leading local AI runtimes. Ollama excels at developer workflow, llama.cpp at maximum performa…
Why Run AI Locally?
Local AI in 2026 is practical on laptops with 16GB+ RAM. The hardware you choose — CPU, integrated GPU, dedicated GPU or Apple Silicon — de…
Why a Pre-Deployment Checklist?
AI compliance is not a single checkbox — it is a structured pre-deployment process covering 10 domains with 50 items. Use this checklist to…
Why Measure AI Transparency?
AI transparency can be measured across seven dimensions — Data, Model, Evaluation, Documentation, Security, Oversight and Auditability — us…