Book Image

Hands-on NLP with NLTK and Scikit-learn [Video]

By : James Cross
Book Image

Hands-on NLP with NLTK and Scikit-learn [Video]

By: James Cross

Overview of this book

There is an overflow of text data online nowadays. As a Python developer, you need to create a new solution using Natural Language Processing for your next project. Your colleagues depend on you to monetize gigabytes of unstructured text data. What do you do? Hands-on NLP with NLTK and scikit-learn is the answer. This course puts you right on the spot, starting off with building a spam classifier in our first video. At the end of the course, you are going to walk away with three NLP applications: a spam filter, a topic classifier, and a sentiment analyzer. There is no need for fancy mathematical theory, just plain English explanations of core NLP concepts and how to apply those using Python libraries. Taking this course will help you to precisely create new applications with Python and NLP. You will be able to build actual solutions backed by machine learning and NLP processing models with ease. All the code and supporting files are available on GitHub at: https://github.com/PacktPublishing/Hands-on-NLP-with-NLTK-and-scikit-learn- This course uses Python 3.6, TensorFlow 1.4, NLTK 2, and scikit-learn 0.19, while not the latest version available, it provides relevant and informative content for legacy users of NLP with NLTK and Scikit-learn.
Table of Contents (6 chapters)
Chapter 2
Spam Classification with an Email Dataset
Content Locked
Section 1
Use an Open Source Dataset, and What Is the Enron Dataset
In this video, we will be getting started with spam classification using an open sourced dataset.