🕸️ Neural Networks Explained Like You're 5
Building AI systems and writing about how they actually work. Master of AI @ University of Technology Sydney. Previously B.Tech CS with focus on IoT. I believe the best way to learn is to explain. That's why I'm documenting tech concepts with simple analogies (@sreekarreddy.com). AWS Certified • Azure AI Certified • Neo4j Professional • Google Data Analytics When not coding: exploring Sydney, working on side projects, and teaching tech to anyone who'll listen.
Brain cells learning together
Day 46 of 149
👉 Full deep-dive with code examples
Brain Made of Layers
Your brain has billions of neurons connected together.
Each neuron:
- Receives signals
- Processes them
- Sends to next neurons
Neural networks copy this idea!
The Structure
Input Layer → Hidden Layers → Output Layer
📷 🧠🧠🧠 🏷️
(raw data) (processing) (answer)
Example: Identifying a cat photo
- Input: Pixels
- Hidden: "I see fur... ears... whiskers..."
- Output: "It's a cat!" 🐱
How It Learns
- Show it a cat photo, labeled "cat"
- Network guesses: "dog?" ❌
- Wrong! Adjust the connections
- Show more examples
- Eventually: "cat!" ✅
Repeat millions of times = smart network!
The Math
Each connection has a "weight" (importance).
Input × Weight = Signal to next neuron
Learning = adjusting weights until answers are right.
In One Sentence
Neural networks are layers of connected units that learn patterns by adjusting connection strengths based on examples.
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