Welcome to the Machine Learning repository! This repository contains Jupyter notebooks that showcase various machine learning algorithms, techniques, and projects.
- Algorithms: Jupyter notebooks demonstrating classic machine learning algorithms like K-Means, Decision Trees, Random Forest, Support Vector Machines (SVM), and more.
- Data Preprocessing: Methods for cleaning, transforming, and preparing data for machine learning.
- Evaluation Metrics: Techniques for assessing the performance of different models, such as accuracy, precision, recall, and F1 score.
- Model Tuning: Hyperparameter tuning and optimization for improving model performance.
- Projects: End-to-end machine learning projects to showcase real-world applications.