randomsearch-cv

Deep dive into tuning ML models like a pro. Master Grid Search, Random Search, and Bayesian Optimization, tame overfitting with regularization, validate like it matters, then automate it all with GridSearchCV & RandomizedSearchCV. Ends with a capstone project where you build and optimize a model from scratch..

A Streamlit web app utilizing Python, scikit-learn, and pandas for used car price prediction. Features data preprocessing (scaling, encoding), Random Forest model optimization with GridSearchCV, and interactive user input handling. Achieves high accuracy (R² score: 0.9028), showcasing skills in machine learning, data engineering, and deployment.

This project predicts California housing prices using machine learning regression models, including Random Forests and Decision Trees. It covers data preprocessing, exploratory analysis, model training, and hyperparameter tuning to optimize performance.

Analisis Sentimen Teks Singkat Bahasa Indonesia dengan Hyperparameter Random Forest

Machine learning model evaluation and hyperparameter tuning using Random Forest, Grid Search CV, and Randomized Search CV on the Wine Quality dataset.