SimpleNode
SimpleNode is a small package for working with Neural Networks in python
Features
- Easily create a Neural Network
- Create Labled Data
- Train the Neural Network using Labled Data
- Save trained models
- Load previously saved models
- Make predictions with new inputs
Example
from NeuralNetwork import NeuralNetwork
// Sample XOR dataset
x = [[0, 0], [0, 1], [1, 0], [1, 1]]
y = [[0, 1], [1, 0], [1, 0], [0, 1]]
Network = NeuralNetwork([2, 3, 2])
// Params: trainDataX, trainDataY, epochs, reportFreq
Network.Learn(x, y, 10, 1)
// Save Network
Network.SaveNetwork("MyNetwork.csv")
// Predict
print( Network.Predict([1, 0]) )
Created by Artyom Yesayan
Metadata
Release files for SimpleNode 0.32
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Source distribution (sdist)
| File | Size | Uploaded | Provenance | |
|---|---|---|---|---|
| SimpleNode-0.32.tar.gz | 4.2 kB | Without provenance | Details |
Built distribution (wheel)
| File | Interpreter | ABI | Platform | Reset |
|---|---|---|---|---|
| SimpleNode-0.32-py3-none-any.whl | Python 3 | none | any | Details |
Total release size: 9.6 kB
Release files / SimpleNode-0.32.tar.gz
| Download URL | SimpleNode-0.32.tar.gz |
|---|---|
| Size | 4.2 kB |
| Tags | Source |
|
SHA-256 checksum How to use checksums |
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Release files / SimpleNode-0.32-py3-none-any.whl
| Download URL | SimpleNode-0.32-py3-none-any.whl |
|---|---|
| Size | 5.4 kB |
| Tags | Python 3 |
|
SHA-256 checksum How to use checksums |
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Uploaded using Trusted Publishing? What is trusted publishing? |
No |
| Uploaded via |
twine/4.0.2 CPython/3.11.7
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Security for SimpleNode 0.32
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