This repository predicts body fat percentage using Lasso and Ridge regression models. It compares their accuracy and performance metrics, offering detailed code and model evaluations in the Jupyter Notebook.
This Jupyter Notebook focuses on credit risk prediction using a Random Forest Classifier. It covers data preprocessing, exploratory data analysis (EDA), model training, and handling class imbalance. Additionally, essential metrics such as precision, recall, F1-score, and confusion matrices are computed to evaluate the model's performance.
Machine Learning Jupyter Notebooks
Add a description, image, and links to the machine-learning-course topic page so that developers can more easily learn about it.
To associate your repository with the machine-learning-course topic, visit your repo's landing page and select "manage topics."