This repository contains examples of various machine learning algorithms implemented in Python using Scikit-learn.
In this repository, you'll find Python scripts that demonstrate the implementation of popular machine learning algorithms using Scikit-learn. Each script focuses on a specific algorithm and provides a step-by-step guide to training the model, making predictions, and evaluating the performance.
The following algorithms are covered:
- Naive Bayes Classifier
- Logistic Regression
- Support Vector Machines (SVM)
- Decision Trees
- Random Forests
- Gradient Boosting
If you'd like to contribute to this repository, feel free to submit pull requests with enhancements, additional algorithms, or bug fixes. Your contributions are highly appreciated!