Skip to content

A basic and friendly guide for explaining what neural networks are and how they work.

License

Notifications You must be signed in to change notification settings

ferlopezm94/neural-networks-intro

Folders and files

NameName
Last commit message
Last commit date

Latest commit

 

History

24 Commits
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 

Repository files navigation

Neural Networks Intro

Welcome!

This is a basic guide for explaining what neural networks are and how they work. We'll go over the basic concepts and even implement a neural network with 2 layers, step by step, in order to understand the important parts involved in the whole learning process.

This guide is not meant to be a rigorous one, but rather a friendly one that allows you to understand how all of the pieces fit together, together with some visual aids to ease the understanding of neural networks.

This basic guide is composed of the following 2 parts (2 notebooks):

  • Part 1 - The basics: in this part we'll go over the basics, implementing the simplest neural network - a perceptron.
  • Part 2 - The hidden layer: in this part we'll implement a neural network with 2 layers (a hidden and output layer), and talk about feedforward, backpropagation, how to prepare a dataset and how to refactor a model into a class.

Be ready to learn a lot of concepts but fear not, I'll try my best to help you entry to this exciting field in a friendly way.


¡Bienvenido!

Esta es una guía básica para explicar qué son las redes neuronales y cómo funcionan. Repasaremos los conceptos básicos e incluso implementaremos una red neuronal con 2 capas, paso a paso, para comprender las partes importantes involucradas en todo el proceso de aprendizaje.

Esta guía no pretende ser rigurosa, sino amigable, que le permita comprender cómo encajan todas las piezas, junto con algunas ayudas visuales para facilitar la comprensión de las redes neuronales.

Esta guía básica se compone de las siguientes 2 partes (2 notebooks):

  • Parte 1 - Lo básico: en esta parte repasaremos los conceptos básicos, implementando la red neuronal más simple: un perceptrón.
  • Parte 2 - La capa oculta: en esta parte implementaremos una red neuronal con 2 capas (una capa oculta y de salida), y hablaremos sobre feedforward, backpropagation, cómo preparar un conjunto de datos y cómo para refactorizar un modelo en una clase.

Prepárate para aprender muchos conceptos, pero no temas, haré mi mejor esfuerzo para ayudarte a ingresar a este emocionante campo de manera amigable.

About

A basic and friendly guide for explaining what neural networks are and how they work.

Resources

License

Stars

Watchers

Forks

Releases

No releases published

Packages

No packages published