Python and TensorFlow: Text Classification -- Part 3

Python and TensorFlow: Text Classification -- Part 3

General Description:
In this series of videos, we will be using the TensorFlow Python module to construct a neural network that distinguishes whether a given movie review is either positive or negative.

We will be obtaining movie reviews from IMDB (Internet Movie Database) and using that as our dataset. The intent of these videos is to showcase the use of TensorFlow as well as showing a simple example of how to construct and use a simple neural network.

This video is part of a series on Machine Learning in Python. The link to the playlist may be accessed here:

Python Code:

If I've helped you, feel free to buy me a beer :)

Do you like the development environment I'm using in this video? It's a customized version of vim that's enhanced for Python development. If you want to see how I set up my vim, I have a series on this here:

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[Saurabhsingh-clpx]

In the first case if we used why we need to create a list of 10000?

[DanielWeikert]

Thanks. Where exactly did you specify the "start" token => 1. I only see the zeropadding.

[averydrago]

How did you know that the integers in the encrypted reviews would correspond with the specific word_index["<>"] ? How did you know the number 2 would be UNK?