Chaoqi Zhang zxs1652

## googlenet.py
from __future__ import print_function
import imageio
from PIL import Image
import numpy as np
import keras

from keras.layers import Input, Dense, Conv2D, MaxPooling2D, AveragePooling2D, ZeroPadding2D, Dropout, Flatten, Concatenate, Reshape, Activation
from keras.models import Model
from keras.regularizers import l2
from keras.optimizers import SGD

## 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

## alexnet_tensorflow.ipynb

      
        
          
            
              
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                zxs1652
                / alexnet_tensorflow.ipynb
            
            
              Created
              March 10, 2021 03:25
                — forked from agrhn/alexnet_tensorflow.ipynb
            
              
                AlexNet_TensorFlow.ipynb
              
          
        
      
        
  
    
    

          
    
      
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	from __future__ import print_function
	import imageio
	from PIL import Image
	import numpy as np
	import keras

	from keras.layers import Input, Dense, Conv2D, MaxPooling2D, AveragePooling2D, ZeroPadding2D, Dropout, Flatten, Concatenate, Reshape, Activation
	from keras.models import Model
	from keras.regularizers import l2
	from keras.optimizers import SGD
	'''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