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Projects in Awesome Lists tagged with data-preprocessing-and-cleaning

A curated list of projects in awesome lists tagged with data-preprocessing-and-cleaning .

https://github.com/usk2003/weather-data-analysis-in-szeged

This repository contains an in-depth analysis of historical weather data from Szeged, Hungary. The project uses Python to clean and process data, generate insightful visualizations, and identify patterns and correlations in weather parameters such as temperature, humidity, and precipitation.

analysis data-preprocessing-and-cleaning jupyter-notebook prediction python szeged weather-analysis

Last synced: 15 Apr 2026

https://github.com/atharvkadammm/calmlytic

An end-to-end machine learning project that predicts anxiety severity using classification models (Naive Bayes, Decision Tree, SVM, Logistic Regression, XGBoost), based on lifestyle, health, and behavioral features.

anxiety-prediction classification csv data-analysis data-preprocessing-and-cleaning data-science data-visualization ensemble-learning logistic-regression machine-learning-algorithms matplotlib mental-health numpy pandas python sci-kit-learn seaborn supervised-learning svm xgboost

Last synced: 21 Jun 2025

https://github.com/amanovishnu/anamoly-detection-using-decision-classifier

the kdd 99 anomaly detection application is a flask web app that predicts anomalies in the kdd 99 dataset using a decision tree classifier. it allows users to input features for prediction and offers a user-friendly interface with real-time predictions and low latency.

anamoly-detection data-preprocessing-and-cleaning decision-tree-classifier flask-application kdd-99-dataset machine-learning machine-learning-algorithms

Last synced: 08 Sep 2025

https://github.com/nashish109/smart-ecommerce-fraud-detection

AI-powered system to detect fraudulent transactions in e-commerce using machine learning. Includes data preprocessing, feature engineering, and classification models like Random Forest and XGBoost. Achieved high accuracy with interpretable results for real-time detection.

classification-report-analysis data-preprocessing-and-cleaning ensemble-learning-with-xgboost feature-engineering graph-attention-networks imbalanced-data-handling machine-learning-models model-evaluation-and-metrics smote-sampling-technique

Last synced: 17 May 2026