Keras input and dense layers

Advanced Deep Learning with Keras

Zach Deane-Mayer

Data Scientist

Course outline

Chapter 1: Introduction to the Keras functional API (Refresher)
Chapter 2: Models with 2 inputs
Chapter 3: Models with 3 inputs
Chapter 4: Multiple outputs

Course Datasets: College basketball data, 1989-2017

Dataset 1: Regular season

Team ID 1
Team ID 2
Home vs Away
Score Difference (Team 1 - Team 2)
Team 1 Score
Team 2 Score
Won vs Lost

Dataset 2: Tournament games

Same as Dataset 1
Also has difference in Seed

Course Datasets: College basketball data, 1989-2017

import pandas as pd
games_season = pd.read_csv('datasets/games_season.csv')
games_season.head()

Out[1]:
   season  team_1  team_2  home  score_diff  score_1  score_2  won
0    1985    3745    6664     0          17       81       64    1
1    1985     126    7493     1           7       77       70    1
2    1985     288    3593     1           7       63       56    1
3    1985    1846    9881     1          16       70       54    1
4    1985    2675   10298     1          12       86       74    1

games_tourney = pd.read_csv('datasets/games_tourney.csv')
games_tourney.head()

Out[2]:
   season  team_1  team_2  home  seed_diff  score_diff  score_1  score_2  won
0    1985     288      73     0         -3          -9       41       50    0
1    1985    5929      73     0          4           6       61       55    1
2    1985    9884      73     0          5          -4       59       63    0
3    1985      73     288     0          3           9       50       41    1
4    1985    3920     410     0          1          -9       54       63    0

Inputs and outputs

Two fundamental parts:

Input layer
Output layer

Inputs

from tensorflow.keras.layers import Input
input_tensor = Input(shape=(1,))

Inputs

from tensorflow.keras.layers import Input
input_tensor = Input(shape=(1,))
print(input_tensor)

KerasTensor(type_spec=TensorSpec(shape=(None, 1), dtype=tf.float32, name='input_1'), name='input_1', description="created by layer 'input_1'")

Outputs

from tensorflow.keras.layers import Dense
output_layer = Dense(1)

Outputs

from tensorflow.keras.layers import Dense
output_layer = Dense(1)
print(output_layer)

<keras.layers.core.dense.Dense object at 0x15df15e80>

Connecting inputs to outputs

from tensorflow.keras.layers import Input, Dense
input_tensor = Input(shape=(1,))
output_layer = Dense(1)
output_tensor = output_layer(input_tensor)

Connecting inputs to outputs

print(output_tensor)

KerasTensor(type_spec=TensorSpec(shape=(None, 1), dtype=tf.float32, name=None), name='dense_1/BiasAdd:0', description="created by layer 'dense_1'")

Let's practice!

Advanced Deep Learning with Keras