Alexandre Alexiades all3xfx

## media-query.css

/*
  ##Device = Desktops
  ##Screen = 1281px to higher resolution desktops
*/

@media (min-width: 1281px) {

  /* CSS */


## classifier_from_little_data_script_1.py
'''This script goes along the blog post
"Building powerful image classification models using very little data"
from blog.keras.io.
It uses data that can be downloaded at:
https://www.kaggle.com/c/dogs-vs-cats/data
In our setup, we:
- created a data/ folder
- created train/ and validation/ subfolders inside data/
- created cats/ and dogs/ subfolders inside train/ and validation/
- put the cat pictures index 0-999 in data/train/cats

## readme.md

      
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                all3xfx
                / readme.md
            
            
              Created
              July 19, 2017 05:26
                — forked from baraldilorenzo/readme.md
            
              
                VGG-16 pre-trained model for Keras
              
          
    ##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

  
## classifier_from_little_data_script_3.py
'''This script goes along the blog post
"Building powerful image classification models using very little data"
from blog.keras.io.
It uses data that can be downloaded at:
https://www.kaggle.com/c/dogs-vs-cats/data
In our setup, we:
- created a data/ folder
- created train/ and validation/ subfolders inside data/
- created cats/ and dogs/ subfolders inside train/ and validation/
- put the cat pictures index 0-999 in data/train/cats

## classifier_from_little_data_script_2.py
'''This script goes along the blog post
"Building powerful image classification models using very little data"
from blog.keras.io.
It uses data that can be downloaded at:
https://www.kaggle.com/c/dogs-vs-cats/data
In our setup, we:
- created a data/ folder
- created train/ and validation/ subfolders inside data/
- created cats/ and dogs/ subfolders inside train/ and validation/
- put the cat pictures index 0-999 in data/train/cats

## GIF-Screencast-OSX.md

      
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                all3xfx
                / GIF-Screencast-OSX.md
            
            
              Created
              April 2, 2017 04:39
                — forked from dergachev/GIF-Screencast-OSX.md
            
              
                OS X Screencast to animated GIF
              
          
    OS X Screencast to animated GIF

This gist shows how to create a GIF screencast using only free OS X tools: QuickTime, ffmpeg, and gifsicle.

Instructions

To capture the video (filesize: 19MB), using the free "QuickTime Player" application:

  
## index.html
<!DOCTYPE html>
<html>
<head>
   <meta name="description" content="This is the form demo of the talk Talking and listening to web pages" />
   <meta charset="utf-8">
   <title>Form demo</title>
<style id="jsbin-css">
body
{
   font-size: 24px;

## index.html
<!DOCTYPE html>
<html>
<head>
<meta name="description" content="Speech Synthesis API demo by Aurelio De Rosa (@AurelioDeRosa)" />
  <meta charset="utf-8">
  <title>Speech Synthesis API demo</title>
<style id="jsbin-css">
.text-to-speech {
    float: right;
    cursor: pointer;

	/*
	##Device = Desktops
	##Screen = 1281px to higher resolution desktops
	*/

	@media (min-width: 1281px) {

	/* CSS */
	'''This script goes along the blog post
	"Building powerful image classification models using very little data"
	from blog.keras.io.
	It uses data that can be downloaded at:
	https://www.kaggle.com/c/dogs-vs-cats/data
	In our setup, we:
	- created a data/ folder
	- created train/ and validation/ subfolders inside data/
	- created cats/ and dogs/ subfolders inside train/ and validation/
	- put the cat pictures index 0-999 in data/train/cats
	<!DOCTYPE html>
	<html>
	<head>
	<meta name="description" content="This is the form demo of the talk Talking and listening to web pages" />
	<meta charset="utf-8">
	<title>Form demo</title>
	<style id="jsbin-css">
	body
	{
	font-size: 24px;