| def dot_product(x, kernel): | |
| """ | |
| Wrapper for dot product operation, in order to be compatible with both | |
| Theano and Tensorflow | |
| Args: | |
| x (): input | |
| kernel (): weights | |
| Returns: | |
| """ | |
| if K.backend() == 'tensorflow': |
##VGG16 model for Keras
This is the Keras model of the 16-layer network used by the VGG team in the ILSVRC-2014 competition.
It has been obtained by directly converting the Caffe model provived by the authors.
Details about the network architecture can be found in the following arXiv paper:
Very Deep Convolutional Networks for Large-Scale Image Recognition
K. Simonyan, A. Zisserman
#RxJS 5 Operators By Example
UPDATE: I have moved the contents of this gist plus more to https://github.com/btroncone/learn-rxjs and http://www.learnrxjs.io. For expanded examples, explanations, and resources, please check out this new location!
A complete list of RxJS 5 operators with easy to understand explanations and runnable examples.
| /** | |
| * curry | |
| * | |
| * var curried = curry(function(a, b, c) { | |
| * console.log(a+b+c); | |
| * }); | |
| * | |
| * | |
| * curried(2)(2)(2); // => 6 | |
| * curried(2,2)(2); // => 6 |
(by @andrestaltz)
If you prefer to watch video tutorials with live-coding, then check out this series I recorded with the same contents as in this article: Egghead.io - Introduction to Reactive Programming.
| <!DOCTYPE HTML> | |
| <html lang="en" ng-app="myApp"> | |
| <head> | |
| <meta charset="utf-8"> | |
| <title>Dynamic Pagination w/ Filtering</title> | |
| <meta name="viewport" content="width=device-width, initial-scale=1.0"> | |
| <meta name="description" content=""> | |
| <meta name="author" content="Kim Maida"> | |
| <!-- JS Libraries --> |