|
You are here |
cracedkey.com | ||
| | | | |
www.laputan.org
|
|
| | | | | While much attention has been focused on high-level software architectural patterns, what is, in effect, the de-facto standard software architecture is seldom discussed. This paper examines the most frequently deployed architecture: the BIG BALL OF MUD | |
| | | | |
objective-see.com
|
|
| | | | | ||
| | | | |
c0de517e.com
|
|
| | | | | Angelo Pesce's homepage & blog on computers, graphics and other things. | |
| | | | |
teddykoker.com
|
|
| | | A few posts back I wrote about a common parameter optimization method known as Gradient Ascent. In this post we will see how a similar method can be used to create a model that can classify data. This time, instead of using gradient ascent to maximize a reward function, we will use gradient descent to minimize a cost function. Lets start by importing all the libraries we need: | ||