cmeuncerpy 0.1.43

Machine learning models implemented in PyTorch and Rust, including Linear Regression and Neural Networks

cmeuncerpy

A Python package for machine learning models with PyTorch and Rust backends. Features high-performance implementations of Linear Regression and Neural Network models.

Installation

pip install cmeuncerpy

Features

• Linear Regression: PyTorch-based implementation with gradient descent optimization
• Neural Network Regression: Flexible multi-layer neural network for regression tasks
• Rust Integration: Performance-critical components implemented in Rust via PyO3

Quick Start

from cmeuncerpy.models import LinearRegression
import numpy as np

# Create model
model = LinearRegression(no_features=2, learning_rate=0.01, max_epochs=100)

# Generate sample data
X_train = np.random.randn(100, 2)
y_train = np.random.randn(100)

# Train model
model.fit(X_train, y_train)

# Make predictions
predictions = model.predict(X_train)

Requirements

• Python 3.9 or higher
• PyTorch 2.0.0+
• NumPy, Pandas, Scikit-learn, Matplotlib, Seaborn

Author

Syed Raza ([e-mail])

License

MIT