Skip to content
Tutorial detailing how to build a multilayer perceptron from scratch
Jupyter Notebook
Branch: master
Clone or download
Permalink
Type Name Latest commit message Commit time
Failed to load latest commit information.
data initial project commit Jul 16, 2019
imgs initial project commit Jul 16, 2019
.gitignore Fixed some things Aug 3, 2019
MLP.ipynb Ran MLP.ipynb added some git stuff Aug 1, 2019
README.md Fixed some things Aug 3, 2019

README.md

Building a multilayer perceptron from scratch

The mathematics and computation that drive neural networks are frequently seen as erudite and impenetrable. A clearly illustrated example of building from scratch a neural network for handwriting recognition is presented in MLP.ipynb. This tutorial provides a step-by-step overview of the mathematics and code used in many modern machine learning algorithms.

Installation

To view this notebook in your browser simply click the MLP.ipynb file above.

To run this notebook locally make sure you have git, python, and Jupyter installed.

Then in a terminal window:

$ git clone https://github.com/KirillShmilovich/MLP-Neural-Network-From-Scrath
$ cd MLP-Neural-Network-From-Scrath
$ jupyter-notebook MLP.ipynb
You can’t perform that action at this time.