I will build machine learning classification models for your health or tabular data

Need to predict an outcome from your dataset, such as a diagnosis, churn, or risk? I build and compare machine learning classification models, and I explain the results in plain language.

What I do:

• Clean your data (missing values, encoding, train/validation split)
• Exploratory analysis with correlation heatmaps and distribution plots
• Train and compare Decision Tree, Random Forest, KNN, and Naïve Bayes
• Tune hyperparameters and evaluate with accuracy, precision, recall, F1, and confusion matrix
• Deliver clean Python code and a short report

Sample work: I built a liver disease prediction model on 1,700 patient records. Random Forest scored 0.907 on the Kaggle leaderboard, beating Decision Tree, KNN, and Naïve Bayes.

Please send: your dataset, the target variable, and your deadline.