Keras is a DL library, originally built on Python, that runs over TensorFlow or Theano. It was developed to make DL implementations faster:
- We call install keras using the following command in your operation system's Command Prompt:
pip install keras
- We start by importing the numpy and pandas library for data manipulation. Also, we set a seed that allows us to reproduce the script's results:
import numpy as np
import pandas as pd
numpy.random.seed(8)
- Next, the sequential model and dense layers are imported from keras.models and keras.layers respectively. Keras models are defined as a sequence of layers. The sequential construct allows the user to configure and add layers. The dense layer allows a user to build a fully connected network:
from keras.models import Sequential
from keras.layers import Dense
- The HR attrition dataset...