--- title: "#data-preprocessing articles | Hashnode" description: "Explore 93 articles tagged #data-preprocessing on Hashnode. Tutorials, guides, and how-tos from the community." url: "https://hashnode.com/tag/data-preprocessing" --- Tag # #data-preprocessing 93 posts · 4 followers [Lakshmi Mahabaleshwara](https://hashnode.com/@lakshmi-mahabalesh) · [Aug 24](https://hashnode.com/posts/what-happens-to-a-medical-image-before-and-after-a-model-sees-it/6a8cac4b80ffa6e1b9da795b) ### [What Happens to a Medical Image Before and After a Model Sees It](https://freecodecamp.org/news/what-happens-to-a-medical-image-before-and-after-a-model-sees-it?utm_source=hashnode&utm_medium=feed) Medical 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 w 18 min read · [freecodecamp.org](https://freecodecamp.org/news/what-happens-to-a-medical-image-before-and-after-a-model-sees-it?utm_source=hashnode&utm_medium=feed) [Shreyash Kadam](https://hashnode.com/@shreyash7) · [Aug 3](https://hashnode.com/posts/outlier-detection-and-treatment/6a70befd18d2546bcda8ce90) ### [Outlier Detection and Treatment](https://outlierdetectionandtreatment.hashnode.dev/outlier-detection-and-treatment?utm_source=hashnode&utm_medium=feed) Outlier detection identifies data points that deviate significantly from the norm using statistical (Z-score, IQR), visual (box plots), or machine learning (Isolation Forest, LOF) methods 6 min read · [outlierdetectionandtreatment.hashnode.dev](https://outlierdetectionandtreatment.hashnode.dev/outlier-detection-and-treatment?utm_source=hashnode&utm_medium=feed) [Nethmi Amasha](https://hashnode.com/@amasha) · [Aug 3](https://hashnode.com/posts/why-do-both-data-preprocessing-and-feature-engineering-handle-missing-values/6a7049a1a7ce9f63fd676fbe) ### [Why Do Both Data Preprocessing and Feature Engineering Handle Missing Values?](https://curiousdeveloperbyamasha.hashnode.dev/why-do-both-data-preprocessing-and-feature-engineering-handle-missing-values?utm_source=hashnode&utm_medium=feed) 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](https://curiousdeveloperbyamasha.hashnode.dev/why-do-both-data-preprocessing-and-feature-engineering-handle-missing-values?utm_source=hashnode&utm_medium=feed) [Lakshmi Mahabaleshwara](https://hashnode.com/@lakshmi-mahabalesh) · [Jun 4](https://hashnode.com/posts/how-to-preprocess-medical-images-for-machine-learning/6a21b25709761aac249473c9) ### [How to Preprocess Medical Images for Machine Learning – A Guide Using Chest X-Rays](https://freecodecamp.org/news/how-to-preprocess-medical-images-for-machine-learning?utm_source=hashnode&utm_medium=feed) Learn how to preprocess chest X-rays for machine learning using data validation, normalization, resizing, and image enhancement. 15 min read · [freecodecamp.org](https://freecodecamp.org/news/how-to-preprocess-medical-images-for-machine-learning?utm_source=hashnode&utm_medium=feed) [Muhammad Raza](https://hashnode.com/@mraza) · [Jun 3](https://hashnode.com/posts/data-cleaning-and-preprocessing/6a204c0befa2df32dbe7724b) ### [Data Cleaning and Preprocessing](https://ablank-slate.hashnode.dev/data-cleaning-and-preprocessing?utm_source=hashnode&utm_medium=feed) Learning how to preprocess datasets easily. 3 min read · [ablank-slate.hashnode.dev](https://ablank-slate.hashnode.dev/data-cleaning-and-preprocessing?utm_source=hashnode&utm_medium=feed) [wajahat taj](https://hashnode.com/@Wajahattaj) · [May 13](https://hashnode.com/posts/building-civicai-part-1-when-no-dataset-exists-you-build-one/6a04c79ea0c1540277687d08) ### [Building CivicAI Part 1: When No Dataset Exists, You Build One](https://ai-ml-datascience-from-scratch.hashnode.dev/building-civicai-part-1-when-no-dataset-exists-you-build-one?utm_source=hashnode&utm_medium=feed) How 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](https://ai-ml-datascience-from-scratch.hashnode.dev/building-civicai-part-1-when-no-dataset-exists-you-build-one?utm_source=hashnode&utm_medium=feed) [ismail zamareh](https://hashnode.com/@ismailzamareh) · [May 6](https://hashnode.com/posts/a-practical-guide-to-tackling-class-imbalance-in-tabular-datasets/69fbbcd69facff139386b4ff) ### [A Practical Guide to Tackling Class Imbalance in Tabular Datasets](https://athar-automation.hashnode.dev/a-practical-guide-to-tackling-class-imbalance-in-tabular-datasets?utm_source=hashnode&utm_medium=feed) Comparative analysis of different categories of solutions for imbalanced tabular datasets — educational tutorial / beginner-friendly explainer with clear steps 9 min read · [athar-automation.hashnode.dev](https://athar-automation.hashnode.dev/a-practical-guide-to-tackling-class-imbalance-in-tabular-datasets?utm_source=hashnode&utm_medium=feed) [Vishal Uttam Mane](https://hashnode.com/@vishal-uttam-mane) · [Apr 30](https://hashnode.com/posts/handling-imbalanced-datasets/69f2dee3b18c978233747065) ### [Handling Imbalanced Datasets](https://vishal-uttam-mane-dataset.hashnode.dev/handling-imbalanced-datasets?utm_source=hashnode&utm_medium=feed) Learn advanced techniques to handle imbalanced datasets in machine learning, including SMOTE, cost-sensitive learning, and ensemble methods for improv 5 min read · [vishal-uttam-mane-dataset.hashnode.dev](https://vishal-uttam-mane-dataset.hashnode.dev/handling-imbalanced-datasets?utm_source=hashnode&utm_medium=feed) [wajahat taj](https://hashnode.com/@Wajahattaj) · [Apr 23](https://hashnode.com/posts/building-a-full-stack-ai-powered-municipal-civic-issue-management-system-from-scratch/69ea8d54904b915438bf4a18) ### [Building a Full-Stack AI-Powered Municipal Civic Issue Management System from Scratch](https://ai-ml-datascience-from-scratch.hashnode.dev/building-a-full-stack-ai-powered-municipal-civic-issue-management-system-from-scratch?utm_source=hashnode&utm_medium=feed) From 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](https://ai-ml-datascience-from-scratch.hashnode.dev/building-a-full-stack-ai-powered-municipal-civic-issue-management-system-from-scratch?utm_source=hashnode&utm_medium=feed) [Abstract Algorithms](https://hashnode.com/@abstractalgorithms) · [Mar 29](https://hashnode.com/posts/feature-engineering-transforming-raw-data-into-ml-ready-features-1/69c8ad4a39ae46954dc91716) ### [Feature Engineering: Transforming Raw Data into ML-Ready Features](https://abstractalgorithms.hashnode.dev/feature-engineering-transforming-raw-data-into-ml-ready-features-1?utm_source=hashnode&utm_medium=feed) Raw data breaks models. Feature engineering fixes it. Build reproducible preprocessing pipelines with scikit-learn. 19 min read · [abstractalgorithms.hashnode.dev](https://abstractalgorithms.hashnode.dev/feature-engineering-transforming-raw-data-into-ml-ready-features-1?utm_source=hashnode&utm_medium=feed)