Dense layer keras

>>> # Create a `Sequential` model and add a Dense layer as the first layer.  
>>> model = tf.keras.models.Sequential()
>>> model.add(tf.keras.Input(shape=(16,)))
>>> model.add(tf.keras.layers.Dense(32, activation='relu'))
>>> # Now the model will take as input arrays of shape (None, 16)  
>>> # and output arrays of shape (None, 32).  
>>> # Note that after the first layer, you don't need to specify  
>>> # the size of the input anymore:  
>>> model.add(tf.keras.layers.Dense(32))
>>> model.output_shape
(None, 32)

Source: keras.io

Dense in keras

Dense layer does the below operation on the input and return the output.
output = activation(dot(input, kernel) + bias)

Densenet python keras

tf.keras.applications.DenseNet169(
    include_top=True,
    weights="imagenet",
    input_tensor=None,
    input_shape=None,
    pooling=None,
    classes=1000,
)

Source: keras.io

Similar codes

0 vote171 views1 answer
Zscore python
Python
0 vote187 views2 answers
Dropna threshold
Python
15 votes180 views3 answers
Python random text generator
Python
0 vote180 views1 answer
Python -m pip install --upgrade
Python
8 votes257 views6 answers
Fibonacci sequence python
Python
0 vote199 views1 answer
You will be passed a file path P and string S on the command line. Output the number of times the string S appears in the file P.
Python
10 votes181 views3 answers
Image to text python
Python
0 vote229 views1 answer
Numpy find columns containing nan
Python
1 vote194 views1 answer
Find the most similar rows in two dataframes
Python
8 votes176 views2 answers
Select first word in string python
Python