This repository contains a collection of common machine learning codes in Python. The following documentation will guide you through the repository content and provide the necessary information to get started.

The repository is organized into various folders, each dedicated to a specific machine learning topic. Currently, the main categories include:

• Regression: Implementations of regression algorithms such as linear regression and logistic regression.
• Classification: Codes related to classification algorithms, including support vector machines, decision trees, and k-nearest neighbors.
• Neural Networks: Examples of neural network implementations using frameworks like TensorFlow or PyTorch.
• Clustering: Clustering algorithms such as K-Means and hierarchical clustering.
• Data Preprocessing: Codes related to data cleaning and preparation for model training.