sandgate-dev

model = Sequential([
    Conv2D(32, (3, 3), input_shape=input_shape, activation='relu'),
    MaxPooling2D(pool_size=(2, 2)),
    Dropout(0.2),
    
    Conv2D(32, (3, 3), activation='relu'),
    MaxPooling2D(pool_size=(2, 2)),
    Dropout(0.2),
    
    Conv2D(64, (3, 3), activation='relu'),

sandgate-dev

model = models.Sequential([
	Conv2D(32, (3, 3), activation='relu', input_shape=(150, 150, 3)),
	MaxPooling2D((2, 2)),
  
	Conv2D(64, (3, 3), activation='relu'),
	MaxPooling2D((2, 2)),
  
	Flatten(),
	Dense(64, activation='relu'),
	Dense(128, activation='relu'),

sandgate-dev

'''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

sandgate-dev

'''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

sandgate-dev

'''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

sandgate-dev

# 'This is a test' should equal 'ThIs Is A TeSt'

def to_weird_case_word(string):
    return "".join(c.upper() if i%2 == 0 else c for i, c in enumerate(string.lower()))
    
def to_weird_case(string):
    return " ".join(to_weird_case_word(str) for str in string.split())
	

sandgate-dev

# The mode is the value that shows up the most in a dataset. A dataset can have 0 or more modes. 
# If no value shows up more than once, the dataset is considered to have no mode value. 
# If two numbers show up the same number of times, that dataset is considered bimodal. 
# Datasets where multiple values all show up the same number of times are considered multimodal. 

def get_mode(data):
  most = max(list(map(data.count, data)))
  return list(set(filter(lambda x: data.count(x) == most, data)))

sandgate-dev

001_convertArrayToObject1.js

A Pen by Stephan Osterburg on CodePen.

License.

sandgate-dev

002_convertObjectToList1.js

A Pen by Stephan Osterburg on CodePen.

License.

sandgate-dev

003_convertArrayToObject2.js

A Pen by Stephan Osterburg on CodePen.

License.