Keras transfer learning

inputs = keras.Input(shape=(150, 150, 3))
# We make sure that the base_model is running in inference mode here,
# by passing `training=False`. This is important for fine-tuning, as you will
# learn in a few paragraphs.
x = base_model(inputs, training=False)
# Convert features of shape `base_model.output_shape[1:]` to vectors
# Use golbal averaging pool instead of flatten in some cases
x = keras.layers.GlobalAveragePooling2D()(x)
# A Dense classifier with a single unit (binary classification)
outputs = keras.layers.Dense(1)(x)
model = keras.Model(inputs, outputs)

Source: keras.io

Similar codes

1 vote197 views1 answer
Plt line of best fit
Python
37 votes232 views5 answers
Get requests python
Python
-1 vote203 views1 answer
Pandas merge_asof direction
Python
0 vote169 views1 answer
Import get object
Python
0 vote196 views1 answer
Vscode python workding directory
Python
7 votes267 views1 answer
How to find the location of a character in a string in python
Python
0 vote194 views1 answer
How add a favicon to django
Python
0 vote182 views1 answer
Python set match two list
Python
0 vote204 views1 answer
Picture as background of seaborn plot python
Python
0 vote317 views1 answer
Python use math
Python