neuronflow 0.1.2

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🔮 NeuronFlow 🔮

A lightweight machine learning library written in Python.

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🌌 Overview

NeuronFlow is a Python package designed for building, training, and evaluating machine learning models. Whether you're a beginner or a seasoned professional, this library provides tools for quick prototyping and production-level model development.

Features include:

• 🧠 Customizable Models: Build custom models from scratch using an intuitive API.
• ⚡ Optimized for Performance: Built-in optimizations for faster training.
• 📊 Evaluation Tools: Built-in metrics and visualizations for evaluating models.
• 💡 Explainability: Model insights for transparency and debugging.

🌟 Tools Available

• Linear Models:

  • Linear Regression
  • Multiple Linear Regression
  • Polynomial Regression

• Classifier Models:

  • Logistic Regression

• Evaluation Metrics:

  • Mean Square Error(MSE)
  • Mean Absolute Error(MAE)
  • Root Mean Square Error(RMSE)
  • R2 Score

🚀 Installation

pip install neuronflow

How To Use

import neuronflow as nf

#Regression
from neuronflow import regerssion
from neuronflow import classifier

#Linear Regression
X=np.array([1,2,3,4])
Y=np.array([5,6,7,8])
linear_model=regression.linear(X,Y)
linear_model.fit() 
#Inference 
linera_value=model.value(np.array([9,10]))

#Classification
x=np.array([[0.1,1.2,1.5,2.0,1.0,2.5],[1.1,.9,1.5,1.8,2.5,.5]])
y=np.array([0,0,1,1,1,0])

logistic_model=classifier.logistic(x,y,lr=0.1)
logistic_model.fit()

logistic_model.predict(x)