Neural Cheat Sheet

# keras https://keras.io/
from keras.models import Sequential
from keras import models
from keras import layers
from keras import optimizers

model = Sequential()
model.add(layers.Dense(50, activation='relu', input_shape=(2000,)))
model.add(layers.Dense(1, activation='relu'))
model.add(layers.Dropout(0.3))

model.compile(loss='categorical_crossentropy', optimizer="SGD", metrics=['accuracy'])
history = model.fit(train, label_train, epochs=120, batch_size=256)

from keras import regularizers
model.add(layers.Dense(50, activation='relu',kernel_regularizer=regularizers.l2(0.005), input_shape=(2000,))) #2 hidden layers


from keras.utils import to_categorical
y_train = to_categorical(y_train)


history.history["acc"]
history.history["loss"]
y_pred = model.predict(test)
model.evaluate(train, label_train)


keras.optimizers:
	SGD
	RMSprop
	Adagrad
	Adadelta
	Adam
	Adamax
	Nadam
	
	
metrics: #https://keras.io/metrics/
	mae
	acc
	binary_accuracy
	sparse_categorical_accuracy
	categorical_accuracy
	top_k_categorical_accuracy

loss: # https://keras.io/losses/
	mean_squared_error
	binary_crossentropy
	
	mean_absolute_error
	mean_absolute_percentage_error
	

## Image data

# 1.	reshape to single vector
X.reshape(-1, 255)

imagenet=inception_v3.InceptionV3(weights='imagenet',include_top=False)
imagenet_new=imagenet.output
new_model = models.Sequential()
new_model.add(imagenet)
new_model.add(GlobalAveragePooling2D())
new_model.add(Dense(1024,activation='relu'))
new_model.add(Dense(1024,activation='relu')) #dense layer 2
new_model.add(Dense(512,activation='relu')) #dense layer 3
new_model.add(Dense(1,activation='sigmoid')) #final layer with softmax activation	
	
	
	
	

 - try overfitting on small sample
 - use dropout + L2 to adjust output
 - if depth increases but error does change, change parameters
  - batch normalization
   - SGD + momentum
  - Beamsearch
  - Xavier initialization, N{0,.01} initialization - initial weights
   - convolution layers
   random search better than grid search
   - check for dead units