Explore >> Select a destination
|
You are here 
|
statisticsblog.com | ||
| | | | |
erikbern.com
|
|
| | | | | I made a New Year's resolution: every plot I make during 2018 will contain uncertainty estimates. Nine months in and I have learned a lot, so I put together a summary of some of the most useful methods. | |
| | | | |
www.kuniga.me
|
|
| | | | | NP-Incompleteness: | |
| | | | |
www.randomservices.org
|
|
| | | | | ||
| | | | |
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: | ||
