Rafael Espericueta shimmeringvoid

## Coursera: Convolutional Neural Networks Papers.md

      
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                shimmeringvoid
                / Coursera: Convolutional Neural Networks Papers.md
            
            
              Created
              January 27, 2018 02:21
                — forked from rubychilds/Coursera: Convolutional Neural Networks Papers.md
            
          
    Classic Networks
LeNet-5: LeCun et al, "Gradient-Based Learning Applied to Document Recognition": http://yann.lecun.com/exdb/publis/pdf/lecun-01a.pdf
AlexNet: Krizhevsky et al, "ImageNet Classification with Deep Convolutional Neural Networks": https://papers.nips.cc/paper/4824-imagenet-classification-with-deep-convolutional-neural-networks.pdf
VGG-16: Simonyan et al, "Very Deep Convolutional Networks for Large-Scale Image Recognition": https://arxiv.org/pdf/1409.1556.pdf
Resnets

  
## 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
	'''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