Tracing Back to the Origins 🧠

This repository contains resources and analyses tracing the development of key foundational concepts in neural networks and deep learning. Each folder represents a significant model or theoretical contribution to the field, along with explanations, code, and other resources.

Getting Started

This repo contains detailed introduction and analyses for the monumental papers and important mathematical theorems throughout the development of artificial intelligence: [MP Neuron, Perceptron, Back-propagation, Cognitron, Neocognitron, Elman Network, NPLM, Universal Approximation Theorem]. Each folder contains resources specific to its topic, including theoretical explanations, code samples, and images where applicable. To explore a specific topic, navigate to the corresponding folder.

1. Read the articles in articles_ENG or articles_CHN for an overview and detailed explanations of each model or concept.
2. Check and run the code samples to exercise your muscles! (if available).
3. Feel free to use the slides or resources in the images folder!

Enjoy your journey! 🧠