We are using the same data as we trained the model on previously using scikit-learn in order to perform apple-to-apple comparison between scikit-learn and the deep learning software Keras. Hence, the data loading steps remain the same:
>>> import numpy as np>> import pandas as pd>>> import matplotlib.pyplot as plt>>> from sklearn.datasets import load_digits>>> from sklearn.model_selection import train_test_split>>> from sklearn.preprocessing import StandardScaler>>> from sklearn.metrics import accuracy_score,classification_report
From here onward, we will be using the Keras library modules. Various optimizers are selected though; we will be using Adam in our model. ...
