Deep Learning with TensorFlow

Source code for titanic classifier

The full code for the implemented classifier is as follows:

from tflearn.datasets import titanic titanic.download_dataset('titanic_dataset.csv') from tflearn.data_utils import load_csv data, labels = load_csv('titanic_dataset.csv', target_column=0,                         categorical_labels=True, n_classes=2) def preprocess(data, columns_to_ignore):     for id in sorted(columns_to_ignore, reverse=True):         [r.pop(id) for r in data]     for i in range(len(data)):         data[i][1] = 1. if data[i][1] == 'female' else 0.     return np.array(data, dtype=np.float32) to_ignore=[1, 6] data = preprocess(data, to_ignore) net = tflearn.input_data(shape=[None, 6]) net = tflearn.fully_connected(net, 32) net = tflearn.fully_connected(net, 32) net = tflearn.fully_connected(net, ...