Difficulty: beginner
Estimated Time: 20 minutes

TensorFlow is the platform enabling building deep Neural Network architectures and performing Deep Learning. Natural Language Processing is the class of problems of using and processing text, This tutorial introduces the basics needed to perform text classification by performing Sentiment Analysis.

In this scenario, you will learn how to use TensorFlow for text classification. The content is based on the official Text classification tutorial.

To take the most of this course, you should know how to program in Python or other languages that would allow you to understand Python syntax. KNowledge on TensorFlow is also valuable.

Congratulations!

You've completed Sentiment Analysis scenario.

You've learned how to:

  • Create a DNN Estimator
  • Train the model
  • Use the model for future predictions

Sentiment analysis

Step 1 of 6

Importing packages

To start working with Python shell run the following command:

python3

You can use quit() to leave it.

To start working you should first import few packages to give Python access to all its assets:

import tensorflow as tf import numpy as np import os import pandas as pd import tensorflow_hub as tf_hub

Some of the helper functions has been defined in the help package. The package contains mostly functions to load the data.

import help