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random-forest-classifier

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virajbhutada / Telecom-Customer-Churn-Prediction

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Predict and prevent customer churn in the telecom industry with our advanced analytics and Machine Learning project. Uncover key factors driving churn and gain valuable insights into customer behavior with interactive Power BI visualizations. Empower your decision-making process with data-driven strategies and improve customer retention.

data-science machine-learning neural-network python-library machine-learning-algorithms eda pandas data-analysis logistic-regression powerbi roc-curve decision-tree-classifier churn-prediction machine-learning-models random-forest-classifier classification-models customer-churn-prediction customer-attrition-analysis xgboost-classifier powerbi-desktop
  • Updated Jun 27, 2024
  • HTML

SimranS22 / Heart-Disease-Prediction-Model-SurTech

Star 2

A ML application(deployed on flask) to detect heart disease in patients based on medical features.

python machine-learning jupyter-notebook data-visualization naive-bayes-classifier data-analysis ensemble-learning logistic-regression decision-tree-classifier svm-classifier random-forest-classifier knn-classifier xgboost-classifier bagging-ensemble github-codespaces adaboost-classifier
  • Updated Jun 26, 2024
  • Jupyter Notebook

oladimeji-kazeem / diabetes-detection-using-ai

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This repository contains code and resources for detecting diabetes using artificial intelligence (AI) techniques. The project leverages machine learning algorithms to predict the likelihood of diabetes based on various medical and demographic factors. The primary goal is to provide a reliable and accurate tool for early detection of diabetes.

machine-learning cross-validation logistic-regression support-vector-machines hyperparameter-tuning k-nearest-neighbours gradient-boosting random-forest-classifier diabetes-prediction
  • Updated Jun 25, 2024
  • Jupyter Notebook

oladimeji-kazeem / bank-customer-churn-predictor

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Customer churn is a critical issue for banks, as retaining customers is more cost-effective than acquiring new ones. This project aims to analyse customer churn in a bank and develop a predictive model to identify customers who are likely to leave, and the responsible factors.

machine-learning banking hyperparameter-optimization logistic-regression svm-classifier random-forest-classifier customer-segmentation xgboost-classifier
  • Updated Jun 24, 2024
  • Jupyter Notebook

StarlangSoftware / Classification

Star 4

Machine learning library for classification tasks

deep-neural-networks feature-selection naive-bayes-classifier pca statistical-tests dataset-manager decision-tree-classifier decision-stumps multilayer-perceptron-network quadratic-discriminant-analysis linear-discriminant-analysis multilayer-perceptron random-forest-classifier subset-selection rocchio-algorithm knn-algorithm support-vector-machine-svm bagging-trees autoencoder-classification classification-algorithms
  • Updated Jun 22, 2024
  • Java

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