LLakshmi Mahabaleshwara·Aug 24What Happens to a Medical Image Before and After a Model Sees ItMedical imaging papers are full of familiar-looking terms: normalization, labels, validation, annotation, and preprocessing. If you come from general machine learning, you may think you already know w18 min read·freecodecamp.org
SShreyash Kadam·Aug 3Outlier Detection and TreatmentOutlier detection identifies data points that deviate significantly from the norm using statistical (Z-score, IQR), visual (box plots), or machine learning (Isolation Forest, LOF) methods6 min read·outlierdetectionandtreatment.hashnode.dev1
NNethmi Amasha·Aug 3Why Do Both Data Preprocessing and Feature Engineering Handle Missing Values?Discover why Data Preprocessing and Feature Engineering both handle missing values and how their purposes differ in machine learning.4 min read·curiousdeveloperbyamasha.hashnode.dev
LLakshmi Mahabaleshwara·Jun 4How to Preprocess Medical Images for Machine Learning – A Guide Using Chest X-RaysLearn how to preprocess chest X-rays for machine learning using data validation, normalization, resizing, and image enhancement.15 min read·freecodecamp.org1
MMuhammad Raza·Jun 3Data Cleaning and PreprocessingLearning how to preprocess datasets easily.3 min read·ablank-slate.hashnode.dev1
Wwajahat taj·May 13Building CivicAI Part 1: When No Dataset Exists, You Build OneHow I built a 1,100-row dataset from scratch for an AI municipal complaint system, formulas, labels, and preprocessing explained.11 min read·ai-ml-datascience-from-scratch.hashnode.dev
Iismail zamareh·May 6A Practical Guide to Tackling Class Imbalance in Tabular DatasetsComparative analysis of different categories of solutions for imbalanced tabular datasets — educational tutorial / beginner-friendly explainer with clear steps9 min read·athar-automation.hashnode.dev
VVishal Uttam Mane·Apr 30Handling Imbalanced DatasetsLearn advanced techniques to handle imbalanced datasets in machine learning, including SMOTE, cost-sensitive learning, and ensemble methods for improv5 min read·vishal-uttam-mane-dataset.hashnode.dev
Wwajahat taj·Apr 23Building a Full-Stack AI-Powered Municipal Civic Issue Management System from ScratchFrom 200 rows to a deployed ML system — NLP, TF-IDF, Logistic Regression, XGBoost, FastAPI, React, and full cloud deployment explained step by step.14 min read·ai-ml-datascience-from-scratch.hashnode.dev
AAbstract Algorithms·Mar 29Feature Engineering: Transforming Raw Data into ML-Ready FeaturesRaw data breaks models. Feature engineering fixes it. Build reproducible preprocessing pipelines with scikit-learn.19 min read·abstractalgorithms.hashnode.dev
