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xgboost-model

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Crisis incidents caused by rebel groups create a negative influence on the political and economic situation of a country. However, information about rebel group activities has always been limited. Sometimes these groups do not take responsibility for their actions, sometimes they falsely claim responsibility for other rebel group’s actions. Thi…

  • Updated Dec 5, 2022
  • Jupyter Notebook

This is a Liver Disease Machine Learning Classification Capstone Project in fulfillment of the Udacity Azure ML Nanodegree. In this project, you will learn to deploy a machine learning model from scratch. The files and documentation with experiment instructions needed for replicating the project, is provided for you.

  • Updated Feb 12, 2021
  • Jupyter Notebook

Using a Kaggle dataset, customer personality was analysed on the basis of their spending habits, income, education, and family size. K-Means, XGBoost, and SHAP Analysis were performed.

  • Updated Nov 4, 2021
  • Jupyter Notebook

The project analyzes battery cycling data to predict degradation patterns and performance metrics using both deep learning (LSTM) and traditional machine learning (XGBoost) approaches. The implementation enables accurate estimation of battery health, which is crucial for battery management systems in various applications.

  • Updated Apr 14, 2025
  • Jupyter Notebook

I'm attempting the NYC Taxi Duration prediction Kaggle challenge. I'll by using a combination of Pandas, Matplotlib, and XGBoost as python libraries to help me understand and analyze the taxi dataset that Kaggle provides. The goal will be to build a predictive model for taxi duration time. I'll also be using Google Colab as my jupyter notebook.…

  • Updated Sep 21, 2018
  • Jupyter Notebook

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