background preloader

Neural Networks

Facebook Twitter

Electrical Engineering and Computer Science. Unsupervised Feature Learning and Deep Learning Tutorial. Problem Formulation As a refresher, we will start by learning how to implement linear regression.

Unsupervised Feature Learning and Deep Learning Tutorial

The main idea is to get familiar with objective functions, computing their gradients and optimizing the objectives over a set of parameters. These basic tools will form the basis for more sophisticated algorithms later. Readers that want additional details may refer to the Lecture Note on Supervised Learning for more. Basic Neural Network Tutorial : C++ Implementation and Source Code. So I’ve now finished the first version of my second neural network tutorial covering the implementation and training of a neural network.

Basic Neural Network Tutorial : C++ Implementation and Source Code

I noticed mistakes and better ways of phrasing things in the first tutorial (thanks for the comments guys) and rewrote large sections. This will probably occur with this tutorial in the coming week so please bear with me. I’m pretty overloaded with work and assignments so I haven’t been able to dedicate as much time as I would have liked to this tutorial, even so I feel its rather complete and any gaps will be filled in by my source code. Introduction & Implementation. Neural networks and deep learning. The human visual system is one of the wonders of the world.

Neural networks and deep learning

Consider the following sequence of handwritten digits: Most people effortlessly recognize those digits as 504192. That ease is deceptive. The Nature of Code. “You can’t process me with a normal brain.” — Charlie Sheen We’re at the end of our story.

The Nature of Code

This is the last official chapter of this book (though I envision additional supplemental material for the website and perhaps new chapters in the future). Neural networks and deep learning. 15 Steps to Implement a Neural Net – code-spot. (Original image by Hljod.Huskona / CC BY-SA 2.0).

15 Steps to Implement a Neural Net – code-spot

I used to hate neural nets. Mostly, I realise now, because I struggled to implement them correctly. Texts explaining the working of neural nets focus heavily on the mathematical mechanics, and this is good for theoretical understanding and correct usage. However, this approach is terrible for the poor implementer, neglecting many of the details that concern him or her. This tutorial is an implementation guide.