PyAiNetwork 0.2.2

A simple Python library for creating neural networks

PyAiNetwork

A lightweight, open-source Python library for building and training neural networks with only a few lines of code.

Create AI models without writing hundreds of lines for neurons, layers, and weights.

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Installation

pip install PyAiNetwork

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Features

• 🚀 Beginner-friendly API
• 🧠 Standard Network
• ⚡ Advanced ProfNetwork
• 🔥 GELU activation
• 🔥 ReLU activation
• 🔥 Sigmoid activation
• 📈 Built-in training
• 🎯 Custom network architectures
• 🪶 Lightweight & fast
• 🐍 Pure Python
• 💚 Open Source

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Quick Start

from PyAiNetwork import Network

net = Network(
    2,      # Input neurons
    2,      # Hidden layers
    4,      # Neurons per hidden layer
    1       # Output neurons
)

result = net.forward([0.5, 1.0])

print(result)

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Training

from PyAiNetwork import Network

net = Network(2, 1, 4, 1)

for _ in range(100):
    net.train(
        [1, 0],
        [1]
    )

print(net.forward([1, 0]))

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Activation Functions

PyAiNetwork supports multiple activation functions.

GELU

Network(..., activition="gelu")

ReLU

Network(..., activition="relu")

Sigmoid

Network(..., activition="sigmoid")

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Network

Network creates a neural network where every hidden layer contains the same number of neurons.

Network(
    input_neurons,
    hidden_layers,
    neurons_per_layer,
    output_neurons,
    activition="gelu"
)

Example

net = Network(
    4,
    3,
    16,
    2
)

Architecture

4 → 16 → 16 → 16 → 2

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ProfNetwork

ProfNetwork allows every hidden layer to have a different number of neurons.

from PyAiNetwork import ProfNetwork

net = ProfNetwork(
    2,
    [8, 16, 8],
    1
)

Architecture

2 → 8 → 16 → 8 → 1

Another example

net = ProfNetwork(
    3,
    [32, 64, 64, 32],
    5
)

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Which one should I use?

Class	Best for
Network	Simple projects and learning
ProfNetwork	Custom architectures and larger AI models

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Roadmap

Planned features for future releases

• Adam Optimizer
• Save / Load models
• Batch training
• More activation functions
• More loss functions
• Better performance
• More neural network types
• GPU support (planned)

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About Eyes Studio

PyAiNetwork is developed by Eyes Studio, an independent software developer focused on AI technologies, developer tools, and open-source software.

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License

MIT License

Copyright © 2026 Eyes Studio

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GitHub

https://github.com/eyes-studio/PyAiNetwork