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catboost-classifier

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This project aims to train the best model for predicting customer churn. In this project; first, data is studied and several diagrams are depicted for storytelling. Since we face with unbalanced data, categorical data, outliers, unscaled data and ecxess of features, related packages from python is utilized to prepare data for modelling.

  • Updated Jan 19, 2025
  • Jupyter Notebook

We all have experienced a time when we have to look up for a new house to buy. But then the journey begins with a lot of frauds, negotiating deals, researching the local areas and so on. So to deal with this kind of issues Today, I prepared a MACHINE LEARNING Based model, trained on the House Price Prediction Dataset.

  • Updated Jun 27, 2023
  • Jupyter Notebook

This repository contains the project where the goal is to develop a machine learning model that can accurately predict car prices based on various features. We explored multiple models including K-Nearest Neighbor, Decision Tree, Catboost Classifier, and Light Gradient Boosting Classifier.

  • Updated May 31, 2023
  • Jupyter Notebook

We all have experienced a time when we have to look up for a new house to buy. But then the journey begins with a lot of frauds, negotiating deals, researching the local areas and so on. So to deal with this kind of issues Today, I prepared a MACHINE LEARNING Based model, trained on the House Price Prediction Dataset.

  • Updated Jun 4, 2024
  • Jupyter Notebook

Built a Machine Learning Supervised classification algorithm, for predicting the risk of cardiovascualar disease withing coming 10 years by analyzing Patients medical History.

  • Updated Apr 16, 2023
  • Jupyter Notebook

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