Document Summarization: Eval First
Build an extractive/abstractive summarization workflow with dataset splits, ROUGE/BERTScore, and human eval checklists.
Practical insights about Python, React, machine learning, and AI.
Build an extractive/abstractive summarization workflow with dataset splits, ROUGE/BERTScore, and human eval checklists.
A practical guide to entity matching using TF-IDF, Jaro-Winkler, and embedding similarity with thresholds and evaluation.
A practical, production-ready text cleaning pipeline for NLP tasks with regex rules, normalization, and evaluation hooks.
RAG is a design pattern, not a product. LangChain supports it out of the box. This guide shows a production-ready RAG setup in LangChain with architecture, retrieval choices, runnable code, evaluation metrics, and trade-offs from my client projects.
LightRAG is a minimal RAG toolkit that strips away heavy abstractions. Here’s a complete build with code, performance numbers versus a LangChain baseline, and when LightRAG is the right choice.
Retrieval-Augmented Generation for Knowledge-Intensive NLP Tasks
Learn the fundamental differences between on-page and off-page SEO strategies and how they work together to boost your search rankings
Complete guide to detecting, analyzing, and handling missing values in pandas DataFrames using fillna, interpolation, and advanced imputation techniques.
Complete guide to outlier detection and removal using IQR, Z-Score, and isolation forest methods with practical Python examples.
Learn when to use reshape() vs flatten() in NumPy for array manipulation, with practical examples and performance comparisons.