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Prediction of Diabetes Using Machine Learning

Kaggle dataset used in the project can be found here: https://www.kaggle.com/uciml/pima-indians-diabetes-database

The aim of the project is to predict whether a person will develop diabetes based on several factors. The project uses three classification machine learning algorithms:

  • Logistic regression
  • Decision tree
  • Random forest

The project includes some common techniques used while working with machine learning algorithms:
  • Exploratory data analysis (EDA)
  • Visualizations
  • Feature engineering
  • Splitting the dataset into training and test sets
  • Standardization
  • Principal component analysis (PCA)
  • Pipelines
  • Cross validation
  • Hyperparameter tuning
  • Model assessment

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Predicting whether a person will become a diabetes based on several diagnostic measurements

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