r/u_elonkingo

Day 7 of building a neural network from scratch in Python (no libraries). & i discover a new networking

were i want to give it as open source were i even made report if you need use it i am do inside of reddit because i don't have a git account

the image above seeing was the simulation of the network 🙄🙄🙄

i well explain this new network in other post that was reson for delay of post

Today I started tracking accuracy.

Until now, I knew the model was learning because the loss was decreasing.

But accuracy makes it clearer:

How often is the model actually correct?

Right now, the accuracy is still low — but it’s improving with each training cycle.

Example:

Epoch 1 → Accuracy: 12%

Epoch 3 → Accuracy: 28%

Epoch 5 → Accuracy: 41%

This might not look impressive yet, but it proves something important:

The model is learning.

Each iteration makes it slightly better than before.

Tomorrow, I’ll focus on improving performance and making training more efficient.

Day 8/30 ✅

I’ll update again tomorrow.

import numpy as np

import random

# --------------------------

# Node Definition

# --------------------------

class Node:

def __init__(self, id):

self.id = id

self.rs = np.random.rand(4) # Resonance Signature

def similarity(self, other_rs):

return np.dot(self.rs, other_rs) / (

np.linalg.norm(self.rs) * np.linalg.norm(other_rs)

)

def receive(self, signal):

print(f"Node {self.id} received: {signal['data']}")

return self.mutate(signal)

def mutate(self, signal):

# Slight mutation

signal['energy'] *= 0.9

return signal

# --------------------------

# Encode Message

# --------------------------

def encode(message):

return {

"data": message,

"energy": 1.0,

}

# --------------------------

# Propagation Engine

# --------------------------

def propagate(sender, nodes, message, threshold=0.7):

signal = encode(message)

active_nodes = [sender]

while signal["energy"] > 0.1:

next_nodes = []

for node in nodes:

if node == sender:

continue

score = sender.similarity(node.rs)

if score > threshold:

signal = node.receive(signal)

next_nodes.append(node)

if not next_nodes:

break

sender = random.choice(next_nodes)

signal["energy"] *= 0.8

# --------------------------

# Simulation

# --------------------------

nodes = [Node(i) for i in range(10)]

sender = nodes[0]

propagate(sender, nodes, "Hello from Resonance Network!")

My neural network is getting better (accuracy tracking) – Day 8/30 & i discover a new networking

I want to give my python code of new networking way to you all just copy the entire text and can you use it properly and useful way because not just uses for only in Limited option if you want I can give you the simulation code also but first i want to give is python codes and i want to see how u us

r/u_elonkingo

My neural network is getting better (accuracy tracking) – Day 8/30 &amp; i discover a new networking

My neural network is getting better (accuracy tracking) – Day 8/30 & i discover a new networking