michael-m-aher / ml-algorithms

Python implimentation of Important Machine Learning Algorithms

Machine Learning Algorithms

Brief

This project focuses on implementing various machine learning models in Python, covering a range of algorithms for classification and regression tasks. The implemented models include:

• K-Means Clustering
• K-Nearest Neighbors (KNN)
• Linear Regression
• Logistic Regression
• Naive Bayes
• Neural Network
• Support Vector Machine (SVM)

Installation

To use this project, you will need Python 3 installed on your system. You can download Python 3 from the official website: Python Downloads

After installing Python 3, you also need to install the required packages. Run the following command in your terminal or command prompt:

pip install numpy matplotlib

Once you have Python 3 and the required packages installed, you can leverage the machine learning models.

Usage

The project is organized into multiple modules, each dedicated to a specific machine learning model. You can use these modules to train and evaluate models on your datasets.

Here is an example of how to use the K-Means clustering module to cluster data:

from k_means import KMeans

# Your data preparation code here

# Instantiate the KMeans class
kmeans_model = KMeans(n_clusters=3)

# Fit the model to your data
kmeans_model.fit(X)

# Get the cluster assignments for each data point
labels = kmeans_model.predict(X)
print(labels)

Contributing

Pull requests are welcome. For major changes, please open an issue first to discuss what you would like to change.

Please make sure to update tests as appropriate.

Author

👤 Michael Maher

• Twitter: @Michael___Maher
• Github: @Michael-M-aher

Show your support

Please ⭐️ this repository if this project helped you!

📝 License

Copyright © 2024 Michael Maher.
This project is MIT licensed.