A custum Python ML package
Project description
Py-Neuronn
Neuronn is a collection of machine learning models implemented from scratch. This library provides simple and easy-to-use implementations of various machine learning algorithms, including linear regression, multiple regression, logistic regression, k-nearest neighbors (KNN), decision trees,random forests,XGB classifier and SVM.
Installation
You can install Neuronn using pip:
pip install Neuronn
Usage
Here an examples of how to use the models provided by Neuron:
Linear Regression
from Neuronn import LinearRegression
import numpy as np
# Example data
X = np.array([[1], [2], [3], [4]])
y = np.array([2, 4, 6, 8])
# Create and train the model
model = LinearRegression(learning_rate=0.01, epochs=1000)
model.fit(X, y)
# Make predictions
predictions = model.predict(X)
print("Predictions:", predictions)
Contributing
Contributions are welcome! Please open an issue or submit a pull request on GitHub.
License
This project is licensed under the MIT License. See the LICENSE file for more details.
Contact
For any questions or feedback, please contact Karthikeyan.
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