This repository contains exercises for practicing scikit-learn, covering various machine learning topics.
Loading Data: Learn to load datasets and prepare them for analysis.
Preprocessing: Practice scaling, encoding, and handling missing data.
Classification: Build classifiers using algorithms like Logistic Regression, Decision Trees, and SVM.
Regression: Perform regression tasks with Linear Regression, Ridge Regression, and Random Forests.
Clustering: Implement K-Means, DBSCAN, and Hierarchical Clustering for clustering tasks.
Model Evaluation: Evaluate models using metrics like accuracy, precision, recall, and ROC curves.