machinelearningpipelines

Email spam classifier built with scikit-learn, comparing Logistic Regression and Naive Bayes on text data.

MLOps project predicting a flower by its petal and sepal features. Deployed on GCP.

Machine learning fraud detection project using Logistic Regression, Random Forest and XGB Booster to classify imbalanced credit card transaction data.

This repository contains the code and resources for building an end-to-end machine learning pipeline. It includes data preprocessing, feature engineering, model training, evaluation, and deployment scripts.