We are now ready to build our classification model on the features we extracted in the previous section. The code for this section is available in the Modeling.ipynb Jupyter Notebook in case you want to run the examples yourself. To start, let's load some essential dependencies:
from sklearn.externals import joblib import keras from keras import models from keras import layers import model_evaluation_utils as meu import matplotlib.pyplot as plt %matplotlib inline
We will use our nifty model evaluation utilities module named model_evaluation_utils to evaluate our classifier and test its performance later on. Let's load up our feature sets and data point class labels now:
train_features = joblib.load('train_tl_features.pkl') ...
