I would like to finish off our time together by looking at a somewhat more modern module that was only recently introduced by Google's machine learning division called tensorflow.
Tensorflow is an open-source machine learning module that is used primarily for its simplified deep learning and neural network abilities. I would like to take some time to introduce the module and solve a few quick problems using tensorflow. The syntax for tensorflow (like PyBrain in Chapter 12, Beyond the Essentials) is a bit different than our normal scikit-learn syntax so I will be going over it step by step. Let's start with some imports:
from sklearn import datasets, metrics import tensorflow as tf import numpy as np from sklearn.cross_validation import train_test_split %matplotlib inline
Our imports from sklearn include train_test_split, datasets, and metrics. We will be utilizing our train-test splits to reduce overfitting, we will use datasets in order to import our iris classification...