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model-evaluation-and-comparison

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tejasOnGit / Stock-Market-Prediction

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This repository explores the analysis and prediction of financial time series data using various machine learning and deep learning techniques. The project focuses on understanding historical index data, extracting meaningful features, and applying regression models and deep learning architectures for forecasting

exploratory-data-analysis feature-engineering data-cleaning deep-learning-for-time-series modeling-techniques model-evaluation-and-comparison
  • Updated Jul 4, 2024
  • Jupyter Notebook

hamna-mahmood / Fake-News-Detection-System-using-ML-DL

Star 2

Fake News Detection System, based on Machine Learning & Deep Learning, trained on 44,000+ news articles using TF-IDF, Logistic Regression, Decision Tree, Random Forest, CNN, and LSTM, achieving up to 99.76% accuracy.

nlp machine-learning deep-learning neural-network random-forest cnn recurrent-neural-networks artificial-intelligence lstm logistic-regression decision-trees model-training model-evaluation-and-comparison misinformation-detection 44k-dataset
  • Updated Jun 5, 2026
  • Python

DogukanErzurum / Data-Mining-Midterm-Projects

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This project aims to provide a comprehensive analysis of three different machine learning problems: classification, clustering, and regression. By utilizing publicly available datasets, we explore essential steps in machine learning workflows, including data preprocessing, feature selection, model training, and evaluation. The purpose is to showcas

visualization clustering regression classification data-preprocessing model-evaluation-and-comparison
  • Updated Dec 8, 2024
  • Jupyter Notebook

sagar31joon / Iris-ML-Pipeline

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A fully modular end-to-end Machine Learning pipeline for Iris classification. Includes data preparation, scaling, model training, evaluation, performance comparison, and a CLI-based prediction system using Logistic Regression, Decision Tree, and SVC. Designed as a clean template for beginners to understand core ML workflow.

exploratory-data-analysis logistic-regression data-preprocessing data-preparation decision-tree-classifier data-handling machine-learning-models support-vector-classifier modular-architecture end-to-end-machine-learning model-serialization model-evaluation-and-comparison cli-system
  • Updated Nov 18, 2025
  • Python

m01ali / HEAPO-Predict

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Predicting daily household heat pump electricity consumption using ML (LR, DT, RF, GBT, ANN) on the HEAPO dataset. Includes SHAP & permutation-based interpretability, subgroup bias analysis, and time-aware evaluation across real-world household, installation, and weather conditions.

data-science exploratory-data-analysis statistical-analysis xgboost hyperparameter-tuning interpretability time-series-forecasting ensemble-methods model-evaluation-and-comparison
  • Updated Apr 21, 2026
  • Python

UK183 / Customer-Churn-Analysis

Star 0

Built an end-to-end Customer Churn Prediction System using ML, achieving 80%+ accuracy with XGBoost. Project includes complete data cleaning, feature engineering, model comparison, & performance evaluation.Key churn drivers such as tenure, monthly charges, internet service, & contract duration were identified through EDA & PowerBI visual insights.

flask machine-learning exploratory-data-analysis business-intelligence data-analytics feature-engineering data-science-portfolio predictive-analytics powerbi xgboost-model classification-models ml-pipeline customer-churn-analysis data-cleaning-and-preprocessing model-evaluation-and-comparison data-driven-decision-making data-analytics-portfolio-project
  • Updated Dec 3, 2025
  • Jupyter Notebook

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