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Using Exploratory Data Analysis(EDA) and building different Machine Learning Models(Logistic Regression, Decision Tree, Random Forest and XGBoost) We'll help Salifort Motors to predict employee turnover rate and retain their talents.
This repository contains PySpark code that implements three machine learning models for predicting diabetes readmission: Decision Forest, Random Forest, and Gradient Boosted models. These models are trained and evaluated using patient information.
All-in-1 notebook which applies different clustering (K-means, hierarchical, fuzzy, optics) and classification (AdaBoost, RandomForest, XGBoost, Custom) techniques for the best model.
Trying to predict survival rate of passengers using algorithms like Logistic Regression, Ada Boost, Gradient Boost , Decision Tree Classifiers , Extra Tree Classifiers , Random Forest Classifiers and XG Boost with appropriate data preprocessing techniques.